Abstract

With the goal to screen high-risk populations for oral cancer in low- and middle-income countries (LMICs), we have developed a low-cost, portable, easy to use smartphone-based intraoral dual-modality imaging platform. In this paper we present an image classification approach based on autofluorescence and white light images using deep learning methods. The information from the autofluorescence and white light image pair is extracted, calculated, and fused to feed the deep learning neural networks. We have investigated and compared the performance of different convolutional neural networks, transfer learning, and several regularization techniques for oral cancer classification. Our experimental results demonstrate the effectiveness of deep learning methods in classifying dual-modal images for oral cancer detection.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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2018 (1)

R. D. Uthoff, B. Song, P. Birur, M. A. Kuriakose, S. Sunny, A. Suresh, S. Patrick, A. Anbarani, O. Spires, P. Wilder-Smith, and R. Liang, “Development of a dual-modality, dual-view smartphone-based imaging system for oral cancer detection,” Proc. SPIE 10486, 104860V (2018).

2017 (6)

A. C. O. V. Le Campion, C. M. B. Ribeiro, R. R. Luiz, F. F. da Silva Júnior, H. C. S. Barros, K. C. B. dos Santos, S. J. Ferreira, L. S. Gonçalves, and S. M. S. Ferreira, “Low survival rates of oral and oropharyngeal squamous cell carcinoma,” Int. J. Dent. 2017, 1–7 (2017).
[Crossref]

K. D. Shield, J. Ferlay, A. Jemal, R. Sankaranarayanan, A. K. Chaturvedi, F. Bray, and I. Soerjomataram, “The global incidence of lip, oral cavity, and pharyngeal cancers by subsite in 2012,” CA Cancer J. Clin. 67(1), 51–64 (2017).
[Crossref] [PubMed]

A. Esteva, B. Kuprel, R. A. Novoa, J. Ko, S. M. Swetter, H. M. Blau, and S. Thrun, “Dermatologist-level classification of skin cancer with deep neural networks,” Nature 542(7639), 115–118 (2017).
[Crossref] [PubMed]

M. Aubreville, C. Knipfer, N. Oetter, C. Jaremenko, E. Rodner, J. Denzler, C. Bohr, H. Neumann, F. Stelzle, and A. Maier, “Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning,” Sci. Rep. 7(1), 11979 (2017).
[Crossref] [PubMed]

M. Halicek, G. Lu, J. V Little, X. Wang, M. Patel, C. C. Griffith, M. W. El-Deiry, A. Y. Chen, and B. Fei, “Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging,” J. Biomed. Opt.  22, 60503–60504 (2017).

G. Litjens, T. Kooi, B. E. Bejnordi, A. A. A. Setio, F. Ciompi, M. Ghafoorian, J. A. W. M. van der Laak, B. van Ginneken, and C. I. Sánchez, “A survey on deep learning in medical image analysis,” Med. Image Anal. 42, 60–88 (2017).
[Crossref] [PubMed]

2016 (4)

P. Mamoshina, A. Vieira, E. Putin, and A. Zhavoronkov, “Applications of Deep Learning in Biomedicine,” Mol. Pharm. 13(5), 1445–1454 (2016).
[Crossref] [PubMed]

V. Gulshan, L. Peng, M. Coram, M. C. Stumpe, D. Wu, A. Narayanaswamy, S. Venugopalan, K. Widner, T. Madams, J. Cuadros, R. Kim, R. Raman, P. C. Nelson, J. L. Mega, and D. R. Webster, “Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs,” JAMA 316(22), 2402–2410 (2016).
[Crossref] [PubMed]

H. C. Shin, H. R. Roth, M. Gao, L. Lu, Z. Xu, I. Nogues, J. Yao, D. Mollura, and R. M. Summers, “Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning,” IEEE Trans. Med. Imaging 35(5), 1285–1298 (2016).
[Crossref] [PubMed]

N. Tajbakhsh, J. Y. Shin, S. R. Gurudu, R. T. Hurst, C. B. Kendall, M. B. Gotway, and Jianming Liang, “Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?” IEEE Trans. Med. Imaging 35(5), 1299–1312 (2016).
[Crossref] [PubMed]

2015 (2)

Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521(7553), 436–444 (2015).
[Crossref] [PubMed]

P. N. Birur, S. P. Sunny, S. Jena, U. Kandasarma, S. Raghavan, B. Ramaswamy, S. P. Shanmugam, S. Patrick, R. Kuriakose, J. Mallaiah, A. Suresh, R. Chigurupati, R. Desai, and M. A. Kuriakose, “Mobile health application for remote oral cancer surveillance,” J. Am. Dent. Assoc. 146(12), 886–894 (2015).
[Crossref] [PubMed]

2014 (2)

M. K. Mallath, D. G. Taylor, R. A. Badwe, G. K. Rath, V. Shanta, C. S. Pramesh, R. Digumarti, P. Sebastian, B. B. Borthakur, A. Kalwar, S. Kapoor, S. Kumar, J. L. Gill, M. A. Kuriakose, H. Malhotra, S. C. Sharma, S. Shukla, L. Viswanath, R. T. Chacko, J. L. Pautu, K. S. Reddy, K. S. Sharma, A. D. Purushotham, and R. Sullivan, “The growing burden of cancer in India: epidemiology and social context,” Lancet Oncol. 15(6), e205–e212 (2014).
[Crossref] [PubMed]

N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, “Dropout: A Simple Way to Prevent Neural Networks from Overfitting,” J. Mach. Learn. Res. 15, 1929–1958 (2014).

2012 (6)

M. C. Pierce, R. A. Schwarz, V. S. Bhattar, S. Mondrik, M. D. Williams, J. J. Lee, R. Richards-Kortum, and A. M. Gillenwater, “Accuracy of in vivo multimodal optical imaging for detection of oral neoplasia,” Cancer Prev. Res. (Phila.) 5(6), 801–809 (2012).
[Crossref] [PubMed]

M. M. R. Krishnan, V. Venkatraghavan, U. R. Acharya, M. Pal, R. R. Paul, L. C. Min, A. K. Ray, J. Chatterjee, and C. Chakraborty, “Automated oral cancer identification using histopathological images: a hybrid feature extraction paradigm,” Micron 43(2-3), 352–364 (2012).
[Crossref] [PubMed]

K. R. Coelho, “Challenges of the oral cancer burden in India,” J. Cancer Epidemiol. 2012, 701932 (2012).
[Crossref] [PubMed]

S. W. Yang, Y. S. Lee, L. C. Chang, C. C. Hwang, and T. A. Chen, “Diagnostic significance of narrow-band imaging for detecting high-grade dysplasia, carcinoma in situ, and carcinoma in oral leukoplakia,” Laryngoscope 122(12), 2754–2761 (2012).
[Crossref] [PubMed]

M. Rana, A. Zapf, M. Kuehle, N.-C. Gellrich, and A. M. Eckardt, “Clinical evaluation of an autofluorescence diagnostic device for oral cancer detection: a prospective randomized diagnostic study,” Eur. J. Cancer Prev. 21(5), 460–466 (2012).
[Crossref] [PubMed]

C. S. Farah, L. McIntosh, A. Georgiou, and M. J. McCullough, “Efficacy of tissue autofluorescence imaging (velscope) in the visualization of oral mucosal lesions,” Head Neck 34(6), 856–862 (2012).
[Crossref]

2011 (1)

K. H. Awan, P. R. Morgan, and S. Warnakulasuriya, “Evaluation of an autofluorescence based imaging system (VELscope™) in the detection of oral potentially malignant disorders and benign keratoses,” Oral Oncol. 47(4), 274–277 (2011).
[Crossref] [PubMed]

2010 (3)

S. J. Pan and Q. Yang, “A Survey on Transfer Learning,” IEEE Trans. Knowl. Data Eng. 22(10), 1345–1359 (2010).
[Crossref]

M. S. Rahman, N. Ingole, D. Roblyer, V. Stepanek, R. Richards-Kortum, A. Gillenwater, S. Shastri, and P. Chaturvedi, “Evaluation of a low-cost, portable imaging system for early detection of oral cancer,” Head Neck Oncol. 2(1), 10 (2010).
[Crossref] [PubMed]

R. Mehrotra, M. Singh, S. Thomas, P. Nair, S. Pandya, N. S. Nigam, and P. Shukla, “A cross-sectional study evaluating chemiluminescence and autofluorescence in the detection of clinically innocuous precancerous and cancerous oral lesions,” J. Am. Dent. Assoc. 141(2), 151–156 (2010).
[Crossref] [PubMed]

2009 (3)

C. F. Poh, C. E. MacAulay, L. Zhang, and M. P. Rosin, “Tracing the “At-Risk” Oral Mucosa Field with Autofluorescence: Steps Toward Clinical Impact,” Cancer Prev. Res. 2(5), 401–404 (2009)

V. Jayaprakash, M. Sullivan, M. Merzianu, N. R. Rigual, T. R. Loree, S. R. Popat, K. B. Moysich, S. Ramananda, T. Johnson, J. R. Marshall, A. D. Hutson, T. S. Mang, B. C. Wilson, S. R. Gill, J. Frustino, A. Bogaards, and M. E. Reid, “Autofluorescence-guided surveillance for oral cancer,” Cancer Prev. Res. 2(11), 966–974 (2009).
[Crossref] [PubMed]

D. Roblyer, C. Kurachi, V. Stepanek, M. D. Williams, A. K. El-Naggar, J. J. Lee, A. M. Gillenwater, and R. Richards-Kortum, “Objective detection and delineation of oral neoplasia using autofluorescence imaging,” Cancer Prev. Res. (Phila.) 2(5), 423–431 (2009).
[Crossref] [PubMed]

2008 (3)

K. C. Maitland, A. M. Gillenwater, M. D. Williams, A. K. El-Naggar, M. R. Descour, and R. R. Richards-Kortum, “In vivo imaging of oral neoplasia using a miniaturized fiber optic confocal reflectance microscope,” Oral Oncol. 44(11), 1059–1066 (2008).
[Crossref] [PubMed]

M. Rahman, P. Chaturvedi, A. Gillenwater, and R. R. Richards-Kortum, “Low-cost, multimodal, portable screening system for early detection of oral cancer,” J. Biomed. Opt.  13, 30502–30503 (2008).

I. Pavlova, M. Williams, A. El-Naggar, R. Richards-Kortum, and A. Gillenwater, “Understanding the Biological Basis of Autofluorescence Imaging for Oral Cancer Detection: High-Resolution Fluorescence Microscopy in Viable Tissue,” Clin. Cancer Res. 14(8), 2396–2404 (2008).

2007 (1)

S. Petti and C. Scully, “Oral cancer knowledge and awareness: primary and secondary effects of an information leaflet,” Oral Oncol. 43(4), 408–415 (2007).
[Crossref] [PubMed]

2006 (1)

P. M. Lane, T. Gilhuly, P. D. Whitehead, H. Zeng, C. Poh, S. Ng, M. Williams, L. Zhang, M. Rosin, and C. E. MacAulay, “Simple device for the direct visualization of oral-cavity tissue fluorescence,” J. Biomed. Opt. 11, 24006–24007 (2006).

2004 (1)

E. Svistun, R. Alizadeh-Naderi, A. El-Naggar, R. Jacob, A. Gillenwater, and R. Richards-Kortum, “Vision enhancement system for detection of oral cavity neoplasia based on autofluorescence,” Head Neck 26(3), 205–215 (2004).
[Crossref] [PubMed]

2000 (2)

H. J. van Staveren, R. L. P. van Veen, O. C. Speelman, M. J. H. Witjes, W. M. Star, and J. L. N. Roodenburg, “Classification of clinical autofluorescence spectra of oral leukoplakia using an artificial neural network: a pilot study,” Oral Oncol. 36(3), 286–293 (2000).
[Crossref] [PubMed]

D. L. Heintzelman, U. Utzinger, H. Fuchs, A. Zuluaga, K. Gossage, A. M. Gillenwater, R. Jacob, B. Kemp, and R. R. Richards-Kortum, “Optimal excitation wavelengths for in vivo detection of oral neoplasia using fluorescence spectroscopy,” Photochem. Photobiol. 72(1), 103–113 (2000).
[Crossref] [PubMed]

1998 (1)

A. Gillenwater, R. Jacob, R. Ganeshappa, B. Kemp, A. K. El-Naggar, J. L. Palmer, G. Clayman, M. F. Mitchell, and R. Richards-Kortum, “Noninvasive diagnosis of oral neoplasia based on fluorescence spectroscopy and native tissue autofluorescence,” Arch. Otolaryngol. Head Neck Surg. 124(11), 1251–1258 (1998).
[Crossref] [PubMed]

Acharya, U. R.

M. M. R. Krishnan, V. Venkatraghavan, U. R. Acharya, M. Pal, R. R. Paul, L. C. Min, A. K. Ray, J. Chatterjee, and C. Chakraborty, “Automated oral cancer identification using histopathological images: a hybrid feature extraction paradigm,” Micron 43(2-3), 352–364 (2012).
[Crossref] [PubMed]

Alizadeh-Naderi, R.

E. Svistun, R. Alizadeh-Naderi, A. El-Naggar, R. Jacob, A. Gillenwater, and R. Richards-Kortum, “Vision enhancement system for detection of oral cavity neoplasia based on autofluorescence,” Head Neck 26(3), 205–215 (2004).
[Crossref] [PubMed]

Anantharaman, R.

R. Anantharaman, V. Anantharaman, and Y. Lee, “Oro Vision: Deep Learning for Classifying Orofacial Diseases,” in 2017 IEEE International Conference on Healthcare Informatics (ICHI) (2017), pp. 39–45.
[Crossref]

Anantharaman, V.

R. Anantharaman, V. Anantharaman, and Y. Lee, “Oro Vision: Deep Learning for Classifying Orofacial Diseases,” in 2017 IEEE International Conference on Healthcare Informatics (ICHI) (2017), pp. 39–45.
[Crossref]

Anbarani, A.

R. D. Uthoff, B. Song, P. Birur, M. A. Kuriakose, S. Sunny, A. Suresh, S. Patrick, A. Anbarani, O. Spires, P. Wilder-Smith, and R. Liang, “Development of a dual-modality, dual-view smartphone-based imaging system for oral cancer detection,” Proc. SPIE 10486, 104860V (2018).

Aubreville, M.

M. Aubreville, C. Knipfer, N. Oetter, C. Jaremenko, E. Rodner, J. Denzler, C. Bohr, H. Neumann, F. Stelzle, and A. Maier, “Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning,” Sci. Rep. 7(1), 11979 (2017).
[Crossref] [PubMed]

Awan, K. H.

K. H. Awan, P. R. Morgan, and S. Warnakulasuriya, “Evaluation of an autofluorescence based imaging system (VELscope™) in the detection of oral potentially malignant disorders and benign keratoses,” Oral Oncol. 47(4), 274–277 (2011).
[Crossref] [PubMed]

Badwe, R. A.

M. K. Mallath, D. G. Taylor, R. A. Badwe, G. K. Rath, V. Shanta, C. S. Pramesh, R. Digumarti, P. Sebastian, B. B. Borthakur, A. Kalwar, S. Kapoor, S. Kumar, J. L. Gill, M. A. Kuriakose, H. Malhotra, S. C. Sharma, S. Shukla, L. Viswanath, R. T. Chacko, J. L. Pautu, K. S. Reddy, K. S. Sharma, A. D. Purushotham, and R. Sullivan, “The growing burden of cancer in India: epidemiology and social context,” Lancet Oncol. 15(6), e205–e212 (2014).
[Crossref] [PubMed]

Barros, H. C. S.

A. C. O. V. Le Campion, C. M. B. Ribeiro, R. R. Luiz, F. F. da Silva Júnior, H. C. S. Barros, K. C. B. dos Santos, S. J. Ferreira, L. S. Gonçalves, and S. M. S. Ferreira, “Low survival rates of oral and oropharyngeal squamous cell carcinoma,” Int. J. Dent. 2017, 1–7 (2017).
[Crossref]

Bejnordi, B. E.

G. Litjens, T. Kooi, B. E. Bejnordi, A. A. A. Setio, F. Ciompi, M. Ghafoorian, J. A. W. M. van der Laak, B. van Ginneken, and C. I. Sánchez, “A survey on deep learning in medical image analysis,” Med. Image Anal. 42, 60–88 (2017).
[Crossref] [PubMed]

Bengio, Y.

Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521(7553), 436–444 (2015).
[Crossref] [PubMed]

Bhattar, V. S.

M. C. Pierce, R. A. Schwarz, V. S. Bhattar, S. Mondrik, M. D. Williams, J. J. Lee, R. Richards-Kortum, and A. M. Gillenwater, “Accuracy of in vivo multimodal optical imaging for detection of oral neoplasia,” Cancer Prev. Res. (Phila.) 5(6), 801–809 (2012).
[Crossref] [PubMed]

Birur, P.

R. D. Uthoff, B. Song, P. Birur, M. A. Kuriakose, S. Sunny, A. Suresh, S. Patrick, A. Anbarani, O. Spires, P. Wilder-Smith, and R. Liang, “Development of a dual-modality, dual-view smartphone-based imaging system for oral cancer detection,” Proc. SPIE 10486, 104860V (2018).

Birur, P. N.

P. N. Birur, S. P. Sunny, S. Jena, U. Kandasarma, S. Raghavan, B. Ramaswamy, S. P. Shanmugam, S. Patrick, R. Kuriakose, J. Mallaiah, A. Suresh, R. Chigurupati, R. Desai, and M. A. Kuriakose, “Mobile health application for remote oral cancer surveillance,” J. Am. Dent. Assoc. 146(12), 886–894 (2015).
[Crossref] [PubMed]

Blau, H. M.

A. Esteva, B. Kuprel, R. A. Novoa, J. Ko, S. M. Swetter, H. M. Blau, and S. Thrun, “Dermatologist-level classification of skin cancer with deep neural networks,” Nature 542(7639), 115–118 (2017).
[Crossref] [PubMed]

Bogaards, A.

V. Jayaprakash, M. Sullivan, M. Merzianu, N. R. Rigual, T. R. Loree, S. R. Popat, K. B. Moysich, S. Ramananda, T. Johnson, J. R. Marshall, A. D. Hutson, T. S. Mang, B. C. Wilson, S. R. Gill, J. Frustino, A. Bogaards, and M. E. Reid, “Autofluorescence-guided surveillance for oral cancer,” Cancer Prev. Res. 2(11), 966–974 (2009).
[Crossref] [PubMed]

Bohr, C.

M. Aubreville, C. Knipfer, N. Oetter, C. Jaremenko, E. Rodner, J. Denzler, C. Bohr, H. Neumann, F. Stelzle, and A. Maier, “Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning,” Sci. Rep. 7(1), 11979 (2017).
[Crossref] [PubMed]

Borthakur, B. B.

M. K. Mallath, D. G. Taylor, R. A. Badwe, G. K. Rath, V. Shanta, C. S. Pramesh, R. Digumarti, P. Sebastian, B. B. Borthakur, A. Kalwar, S. Kapoor, S. Kumar, J. L. Gill, M. A. Kuriakose, H. Malhotra, S. C. Sharma, S. Shukla, L. Viswanath, R. T. Chacko, J. L. Pautu, K. S. Reddy, K. S. Sharma, A. D. Purushotham, and R. Sullivan, “The growing burden of cancer in India: epidemiology and social context,” Lancet Oncol. 15(6), e205–e212 (2014).
[Crossref] [PubMed]

Bray, F.

K. D. Shield, J. Ferlay, A. Jemal, R. Sankaranarayanan, A. K. Chaturvedi, F. Bray, and I. Soerjomataram, “The global incidence of lip, oral cavity, and pharyngeal cancers by subsite in 2012,” CA Cancer J. Clin. 67(1), 51–64 (2017).
[Crossref] [PubMed]

Chacko, R. T.

M. K. Mallath, D. G. Taylor, R. A. Badwe, G. K. Rath, V. Shanta, C. S. Pramesh, R. Digumarti, P. Sebastian, B. B. Borthakur, A. Kalwar, S. Kapoor, S. Kumar, J. L. Gill, M. A. Kuriakose, H. Malhotra, S. C. Sharma, S. Shukla, L. Viswanath, R. T. Chacko, J. L. Pautu, K. S. Reddy, K. S. Sharma, A. D. Purushotham, and R. Sullivan, “The growing burden of cancer in India: epidemiology and social context,” Lancet Oncol. 15(6), e205–e212 (2014).
[Crossref] [PubMed]

Chakraborty, C.

M. M. R. Krishnan, V. Venkatraghavan, U. R. Acharya, M. Pal, R. R. Paul, L. C. Min, A. K. Ray, J. Chatterjee, and C. Chakraborty, “Automated oral cancer identification using histopathological images: a hybrid feature extraction paradigm,” Micron 43(2-3), 352–364 (2012).
[Crossref] [PubMed]

Chang, L. C.

S. W. Yang, Y. S. Lee, L. C. Chang, C. C. Hwang, and T. A. Chen, “Diagnostic significance of narrow-band imaging for detecting high-grade dysplasia, carcinoma in situ, and carcinoma in oral leukoplakia,” Laryngoscope 122(12), 2754–2761 (2012).
[Crossref] [PubMed]

Chatterjee, J.

M. M. R. Krishnan, V. Venkatraghavan, U. R. Acharya, M. Pal, R. R. Paul, L. C. Min, A. K. Ray, J. Chatterjee, and C. Chakraborty, “Automated oral cancer identification using histopathological images: a hybrid feature extraction paradigm,” Micron 43(2-3), 352–364 (2012).
[Crossref] [PubMed]

Chaturvedi, A. K.

K. D. Shield, J. Ferlay, A. Jemal, R. Sankaranarayanan, A. K. Chaturvedi, F. Bray, and I. Soerjomataram, “The global incidence of lip, oral cavity, and pharyngeal cancers by subsite in 2012,” CA Cancer J. Clin. 67(1), 51–64 (2017).
[Crossref] [PubMed]

Chaturvedi, P.

M. S. Rahman, N. Ingole, D. Roblyer, V. Stepanek, R. Richards-Kortum, A. Gillenwater, S. Shastri, and P. Chaturvedi, “Evaluation of a low-cost, portable imaging system for early detection of oral cancer,” Head Neck Oncol. 2(1), 10 (2010).
[Crossref] [PubMed]

M. Rahman, P. Chaturvedi, A. Gillenwater, and R. R. Richards-Kortum, “Low-cost, multimodal, portable screening system for early detection of oral cancer,” J. Biomed. Opt.  13, 30502–30503 (2008).

Chen, A. Y.

M. Halicek, G. Lu, J. V Little, X. Wang, M. Patel, C. C. Griffith, M. W. El-Deiry, A. Y. Chen, and B. Fei, “Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging,” J. Biomed. Opt.  22, 60503–60504 (2017).

Chen, T. A.

S. W. Yang, Y. S. Lee, L. C. Chang, C. C. Hwang, and T. A. Chen, “Diagnostic significance of narrow-band imaging for detecting high-grade dysplasia, carcinoma in situ, and carcinoma in oral leukoplakia,” Laryngoscope 122(12), 2754–2761 (2012).
[Crossref] [PubMed]

Chigurupati, R.

P. N. Birur, S. P. Sunny, S. Jena, U. Kandasarma, S. Raghavan, B. Ramaswamy, S. P. Shanmugam, S. Patrick, R. Kuriakose, J. Mallaiah, A. Suresh, R. Chigurupati, R. Desai, and M. A. Kuriakose, “Mobile health application for remote oral cancer surveillance,” J. Am. Dent. Assoc. 146(12), 886–894 (2015).
[Crossref] [PubMed]

Ciompi, F.

G. Litjens, T. Kooi, B. E. Bejnordi, A. A. A. Setio, F. Ciompi, M. Ghafoorian, J. A. W. M. van der Laak, B. van Ginneken, and C. I. Sánchez, “A survey on deep learning in medical image analysis,” Med. Image Anal. 42, 60–88 (2017).
[Crossref] [PubMed]

Clayman, G.

A. Gillenwater, R. Jacob, R. Ganeshappa, B. Kemp, A. K. El-Naggar, J. L. Palmer, G. Clayman, M. F. Mitchell, and R. Richards-Kortum, “Noninvasive diagnosis of oral neoplasia based on fluorescence spectroscopy and native tissue autofluorescence,” Arch. Otolaryngol. Head Neck Surg. 124(11), 1251–1258 (1998).
[Crossref] [PubMed]

Coelho, K. R.

K. R. Coelho, “Challenges of the oral cancer burden in India,” J. Cancer Epidemiol. 2012, 701932 (2012).
[Crossref] [PubMed]

Coram, M.

V. Gulshan, L. Peng, M. Coram, M. C. Stumpe, D. Wu, A. Narayanaswamy, S. Venugopalan, K. Widner, T. Madams, J. Cuadros, R. Kim, R. Raman, P. C. Nelson, J. L. Mega, and D. R. Webster, “Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs,” JAMA 316(22), 2402–2410 (2016).
[Crossref] [PubMed]

Cuadros, J.

V. Gulshan, L. Peng, M. Coram, M. C. Stumpe, D. Wu, A. Narayanaswamy, S. Venugopalan, K. Widner, T. Madams, J. Cuadros, R. Kim, R. Raman, P. C. Nelson, J. L. Mega, and D. R. Webster, “Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs,” JAMA 316(22), 2402–2410 (2016).
[Crossref] [PubMed]

da Silva Júnior, F. F.

A. C. O. V. Le Campion, C. M. B. Ribeiro, R. R. Luiz, F. F. da Silva Júnior, H. C. S. Barros, K. C. B. dos Santos, S. J. Ferreira, L. S. Gonçalves, and S. M. S. Ferreira, “Low survival rates of oral and oropharyngeal squamous cell carcinoma,” Int. J. Dent. 2017, 1–7 (2017).
[Crossref]

Deng, J.

J. Deng, W. Dong, R. Socher, L. J. Li, K. Li, and L. Fei-Fei, “ImageNet: A large-scale hierarchical image database,” in 2009 IEEE Conference on Computer Vision and Pattern Recognition (2009), pp. 248–255.
[Crossref]

Denzler, J.

M. Aubreville, C. Knipfer, N. Oetter, C. Jaremenko, E. Rodner, J. Denzler, C. Bohr, H. Neumann, F. Stelzle, and A. Maier, “Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning,” Sci. Rep. 7(1), 11979 (2017).
[Crossref] [PubMed]

Desai, R.

P. N. Birur, S. P. Sunny, S. Jena, U. Kandasarma, S. Raghavan, B. Ramaswamy, S. P. Shanmugam, S. Patrick, R. Kuriakose, J. Mallaiah, A. Suresh, R. Chigurupati, R. Desai, and M. A. Kuriakose, “Mobile health application for remote oral cancer surveillance,” J. Am. Dent. Assoc. 146(12), 886–894 (2015).
[Crossref] [PubMed]

Descour, M. R.

K. C. Maitland, A. M. Gillenwater, M. D. Williams, A. K. El-Naggar, M. R. Descour, and R. R. Richards-Kortum, “In vivo imaging of oral neoplasia using a miniaturized fiber optic confocal reflectance microscope,” Oral Oncol. 44(11), 1059–1066 (2008).
[Crossref] [PubMed]

Digumarti, R.

M. K. Mallath, D. G. Taylor, R. A. Badwe, G. K. Rath, V. Shanta, C. S. Pramesh, R. Digumarti, P. Sebastian, B. B. Borthakur, A. Kalwar, S. Kapoor, S. Kumar, J. L. Gill, M. A. Kuriakose, H. Malhotra, S. C. Sharma, S. Shukla, L. Viswanath, R. T. Chacko, J. L. Pautu, K. S. Reddy, K. S. Sharma, A. D. Purushotham, and R. Sullivan, “The growing burden of cancer in India: epidemiology and social context,” Lancet Oncol. 15(6), e205–e212 (2014).
[Crossref] [PubMed]

Dong, W.

J. Deng, W. Dong, R. Socher, L. J. Li, K. Li, and L. Fei-Fei, “ImageNet: A large-scale hierarchical image database,” in 2009 IEEE Conference on Computer Vision and Pattern Recognition (2009), pp. 248–255.
[Crossref]

dos Santos, K. C. B.

A. C. O. V. Le Campion, C. M. B. Ribeiro, R. R. Luiz, F. F. da Silva Júnior, H. C. S. Barros, K. C. B. dos Santos, S. J. Ferreira, L. S. Gonçalves, and S. M. S. Ferreira, “Low survival rates of oral and oropharyngeal squamous cell carcinoma,” Int. J. Dent. 2017, 1–7 (2017).
[Crossref]

Eckardt, A. M.

M. Rana, A. Zapf, M. Kuehle, N.-C. Gellrich, and A. M. Eckardt, “Clinical evaluation of an autofluorescence diagnostic device for oral cancer detection: a prospective randomized diagnostic study,” Eur. J. Cancer Prev. 21(5), 460–466 (2012).
[Crossref] [PubMed]

El-Deiry, M. W.

M. Halicek, G. Lu, J. V Little, X. Wang, M. Patel, C. C. Griffith, M. W. El-Deiry, A. Y. Chen, and B. Fei, “Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging,” J. Biomed. Opt.  22, 60503–60504 (2017).

El-Naggar, A.

I. Pavlova, M. Williams, A. El-Naggar, R. Richards-Kortum, and A. Gillenwater, “Understanding the Biological Basis of Autofluorescence Imaging for Oral Cancer Detection: High-Resolution Fluorescence Microscopy in Viable Tissue,” Clin. Cancer Res. 14(8), 2396–2404 (2008).

E. Svistun, R. Alizadeh-Naderi, A. El-Naggar, R. Jacob, A. Gillenwater, and R. Richards-Kortum, “Vision enhancement system for detection of oral cavity neoplasia based on autofluorescence,” Head Neck 26(3), 205–215 (2004).
[Crossref] [PubMed]

El-Naggar, A. K.

D. Roblyer, C. Kurachi, V. Stepanek, M. D. Williams, A. K. El-Naggar, J. J. Lee, A. M. Gillenwater, and R. Richards-Kortum, “Objective detection and delineation of oral neoplasia using autofluorescence imaging,” Cancer Prev. Res. (Phila.) 2(5), 423–431 (2009).
[Crossref] [PubMed]

K. C. Maitland, A. M. Gillenwater, M. D. Williams, A. K. El-Naggar, M. R. Descour, and R. R. Richards-Kortum, “In vivo imaging of oral neoplasia using a miniaturized fiber optic confocal reflectance microscope,” Oral Oncol. 44(11), 1059–1066 (2008).
[Crossref] [PubMed]

A. Gillenwater, R. Jacob, R. Ganeshappa, B. Kemp, A. K. El-Naggar, J. L. Palmer, G. Clayman, M. F. Mitchell, and R. Richards-Kortum, “Noninvasive diagnosis of oral neoplasia based on fluorescence spectroscopy and native tissue autofluorescence,” Arch. Otolaryngol. Head Neck Surg. 124(11), 1251–1258 (1998).
[Crossref] [PubMed]

Esteva, A.

A. Esteva, B. Kuprel, R. A. Novoa, J. Ko, S. M. Swetter, H. M. Blau, and S. Thrun, “Dermatologist-level classification of skin cancer with deep neural networks,” Nature 542(7639), 115–118 (2017).
[Crossref] [PubMed]

Farah, C. S.

C. S. Farah, L. McIntosh, A. Georgiou, and M. J. McCullough, “Efficacy of tissue autofluorescence imaging (velscope) in the visualization of oral mucosal lesions,” Head Neck 34(6), 856–862 (2012).
[Crossref]

Fei, B.

M. Halicek, G. Lu, J. V Little, X. Wang, M. Patel, C. C. Griffith, M. W. El-Deiry, A. Y. Chen, and B. Fei, “Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging,” J. Biomed. Opt.  22, 60503–60504 (2017).

Fei-Fei, L.

J. Deng, W. Dong, R. Socher, L. J. Li, K. Li, and L. Fei-Fei, “ImageNet: A large-scale hierarchical image database,” in 2009 IEEE Conference on Computer Vision and Pattern Recognition (2009), pp. 248–255.
[Crossref]

Ferlay, J.

K. D. Shield, J. Ferlay, A. Jemal, R. Sankaranarayanan, A. K. Chaturvedi, F. Bray, and I. Soerjomataram, “The global incidence of lip, oral cavity, and pharyngeal cancers by subsite in 2012,” CA Cancer J. Clin. 67(1), 51–64 (2017).
[Crossref] [PubMed]

Ferreira, S. J.

A. C. O. V. Le Campion, C. M. B. Ribeiro, R. R. Luiz, F. F. da Silva Júnior, H. C. S. Barros, K. C. B. dos Santos, S. J. Ferreira, L. S. Gonçalves, and S. M. S. Ferreira, “Low survival rates of oral and oropharyngeal squamous cell carcinoma,” Int. J. Dent. 2017, 1–7 (2017).
[Crossref]

Ferreira, S. M. S.

A. C. O. V. Le Campion, C. M. B. Ribeiro, R. R. Luiz, F. F. da Silva Júnior, H. C. S. Barros, K. C. B. dos Santos, S. J. Ferreira, L. S. Gonçalves, and S. M. S. Ferreira, “Low survival rates of oral and oropharyngeal squamous cell carcinoma,” Int. J. Dent. 2017, 1–7 (2017).
[Crossref]

Frustino, J.

V. Jayaprakash, M. Sullivan, M. Merzianu, N. R. Rigual, T. R. Loree, S. R. Popat, K. B. Moysich, S. Ramananda, T. Johnson, J. R. Marshall, A. D. Hutson, T. S. Mang, B. C. Wilson, S. R. Gill, J. Frustino, A. Bogaards, and M. E. Reid, “Autofluorescence-guided surveillance for oral cancer,” Cancer Prev. Res. 2(11), 966–974 (2009).
[Crossref] [PubMed]

Fuchs, H.

D. L. Heintzelman, U. Utzinger, H. Fuchs, A. Zuluaga, K. Gossage, A. M. Gillenwater, R. Jacob, B. Kemp, and R. R. Richards-Kortum, “Optimal excitation wavelengths for in vivo detection of oral neoplasia using fluorescence spectroscopy,” Photochem. Photobiol. 72(1), 103–113 (2000).
[Crossref] [PubMed]

Ganeshappa, R.

A. Gillenwater, R. Jacob, R. Ganeshappa, B. Kemp, A. K. El-Naggar, J. L. Palmer, G. Clayman, M. F. Mitchell, and R. Richards-Kortum, “Noninvasive diagnosis of oral neoplasia based on fluorescence spectroscopy and native tissue autofluorescence,” Arch. Otolaryngol. Head Neck Surg. 124(11), 1251–1258 (1998).
[Crossref] [PubMed]

Gao, M.

H. C. Shin, H. R. Roth, M. Gao, L. Lu, Z. Xu, I. Nogues, J. Yao, D. Mollura, and R. M. Summers, “Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning,” IEEE Trans. Med. Imaging 35(5), 1285–1298 (2016).
[Crossref] [PubMed]

Gellrich, N.-C.

M. Rana, A. Zapf, M. Kuehle, N.-C. Gellrich, and A. M. Eckardt, “Clinical evaluation of an autofluorescence diagnostic device for oral cancer detection: a prospective randomized diagnostic study,” Eur. J. Cancer Prev. 21(5), 460–466 (2012).
[Crossref] [PubMed]

Georgiou, A.

C. S. Farah, L. McIntosh, A. Georgiou, and M. J. McCullough, “Efficacy of tissue autofluorescence imaging (velscope) in the visualization of oral mucosal lesions,” Head Neck 34(6), 856–862 (2012).
[Crossref]

Ghafoorian, M.

G. Litjens, T. Kooi, B. E. Bejnordi, A. A. A. Setio, F. Ciompi, M. Ghafoorian, J. A. W. M. van der Laak, B. van Ginneken, and C. I. Sánchez, “A survey on deep learning in medical image analysis,” Med. Image Anal. 42, 60–88 (2017).
[Crossref] [PubMed]

Gilhuly, T.

P. M. Lane, T. Gilhuly, P. D. Whitehead, H. Zeng, C. Poh, S. Ng, M. Williams, L. Zhang, M. Rosin, and C. E. MacAulay, “Simple device for the direct visualization of oral-cavity tissue fluorescence,” J. Biomed. Opt. 11, 24006–24007 (2006).

Gill, J. L.

M. K. Mallath, D. G. Taylor, R. A. Badwe, G. K. Rath, V. Shanta, C. S. Pramesh, R. Digumarti, P. Sebastian, B. B. Borthakur, A. Kalwar, S. Kapoor, S. Kumar, J. L. Gill, M. A. Kuriakose, H. Malhotra, S. C. Sharma, S. Shukla, L. Viswanath, R. T. Chacko, J. L. Pautu, K. S. Reddy, K. S. Sharma, A. D. Purushotham, and R. Sullivan, “The growing burden of cancer in India: epidemiology and social context,” Lancet Oncol. 15(6), e205–e212 (2014).
[Crossref] [PubMed]

Gill, S. R.

V. Jayaprakash, M. Sullivan, M. Merzianu, N. R. Rigual, T. R. Loree, S. R. Popat, K. B. Moysich, S. Ramananda, T. Johnson, J. R. Marshall, A. D. Hutson, T. S. Mang, B. C. Wilson, S. R. Gill, J. Frustino, A. Bogaards, and M. E. Reid, “Autofluorescence-guided surveillance for oral cancer,” Cancer Prev. Res. 2(11), 966–974 (2009).
[Crossref] [PubMed]

Gillenwater, A.

M. S. Rahman, N. Ingole, D. Roblyer, V. Stepanek, R. Richards-Kortum, A. Gillenwater, S. Shastri, and P. Chaturvedi, “Evaluation of a low-cost, portable imaging system for early detection of oral cancer,” Head Neck Oncol. 2(1), 10 (2010).
[Crossref] [PubMed]

I. Pavlova, M. Williams, A. El-Naggar, R. Richards-Kortum, and A. Gillenwater, “Understanding the Biological Basis of Autofluorescence Imaging for Oral Cancer Detection: High-Resolution Fluorescence Microscopy in Viable Tissue,” Clin. Cancer Res. 14(8), 2396–2404 (2008).

M. Rahman, P. Chaturvedi, A. Gillenwater, and R. R. Richards-Kortum, “Low-cost, multimodal, portable screening system for early detection of oral cancer,” J. Biomed. Opt.  13, 30502–30503 (2008).

E. Svistun, R. Alizadeh-Naderi, A. El-Naggar, R. Jacob, A. Gillenwater, and R. Richards-Kortum, “Vision enhancement system for detection of oral cavity neoplasia based on autofluorescence,” Head Neck 26(3), 205–215 (2004).
[Crossref] [PubMed]

A. Gillenwater, R. Jacob, R. Ganeshappa, B. Kemp, A. K. El-Naggar, J. L. Palmer, G. Clayman, M. F. Mitchell, and R. Richards-Kortum, “Noninvasive diagnosis of oral neoplasia based on fluorescence spectroscopy and native tissue autofluorescence,” Arch. Otolaryngol. Head Neck Surg. 124(11), 1251–1258 (1998).
[Crossref] [PubMed]

Gillenwater, A. M.

M. C. Pierce, R. A. Schwarz, V. S. Bhattar, S. Mondrik, M. D. Williams, J. J. Lee, R. Richards-Kortum, and A. M. Gillenwater, “Accuracy of in vivo multimodal optical imaging for detection of oral neoplasia,” Cancer Prev. Res. (Phila.) 5(6), 801–809 (2012).
[Crossref] [PubMed]

D. Roblyer, C. Kurachi, V. Stepanek, M. D. Williams, A. K. El-Naggar, J. J. Lee, A. M. Gillenwater, and R. Richards-Kortum, “Objective detection and delineation of oral neoplasia using autofluorescence imaging,” Cancer Prev. Res. (Phila.) 2(5), 423–431 (2009).
[Crossref] [PubMed]

K. C. Maitland, A. M. Gillenwater, M. D. Williams, A. K. El-Naggar, M. R. Descour, and R. R. Richards-Kortum, “In vivo imaging of oral neoplasia using a miniaturized fiber optic confocal reflectance microscope,” Oral Oncol. 44(11), 1059–1066 (2008).
[Crossref] [PubMed]

D. L. Heintzelman, U. Utzinger, H. Fuchs, A. Zuluaga, K. Gossage, A. M. Gillenwater, R. Jacob, B. Kemp, and R. R. Richards-Kortum, “Optimal excitation wavelengths for in vivo detection of oral neoplasia using fluorescence spectroscopy,” Photochem. Photobiol. 72(1), 103–113 (2000).
[Crossref] [PubMed]

Gonçalves, L. S.

A. C. O. V. Le Campion, C. M. B. Ribeiro, R. R. Luiz, F. F. da Silva Júnior, H. C. S. Barros, K. C. B. dos Santos, S. J. Ferreira, L. S. Gonçalves, and S. M. S. Ferreira, “Low survival rates of oral and oropharyngeal squamous cell carcinoma,” Int. J. Dent. 2017, 1–7 (2017).
[Crossref]

Gossage, K.

D. L. Heintzelman, U. Utzinger, H. Fuchs, A. Zuluaga, K. Gossage, A. M. Gillenwater, R. Jacob, B. Kemp, and R. R. Richards-Kortum, “Optimal excitation wavelengths for in vivo detection of oral neoplasia using fluorescence spectroscopy,” Photochem. Photobiol. 72(1), 103–113 (2000).
[Crossref] [PubMed]

Gotway, M. B.

N. Tajbakhsh, J. Y. Shin, S. R. Gurudu, R. T. Hurst, C. B. Kendall, M. B. Gotway, and Jianming Liang, “Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?” IEEE Trans. Med. Imaging 35(5), 1299–1312 (2016).
[Crossref] [PubMed]

Griffith, C. C.

M. Halicek, G. Lu, J. V Little, X. Wang, M. Patel, C. C. Griffith, M. W. El-Deiry, A. Y. Chen, and B. Fei, “Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging,” J. Biomed. Opt.  22, 60503–60504 (2017).

Gulshan, V.

V. Gulshan, L. Peng, M. Coram, M. C. Stumpe, D. Wu, A. Narayanaswamy, S. Venugopalan, K. Widner, T. Madams, J. Cuadros, R. Kim, R. Raman, P. C. Nelson, J. L. Mega, and D. R. Webster, “Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs,” JAMA 316(22), 2402–2410 (2016).
[Crossref] [PubMed]

Gurudu, S. R.

N. Tajbakhsh, J. Y. Shin, S. R. Gurudu, R. T. Hurst, C. B. Kendall, M. B. Gotway, and Jianming Liang, “Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?” IEEE Trans. Med. Imaging 35(5), 1299–1312 (2016).
[Crossref] [PubMed]

Halicek, M.

M. Halicek, G. Lu, J. V Little, X. Wang, M. Patel, C. C. Griffith, M. W. El-Deiry, A. Y. Chen, and B. Fei, “Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging,” J. Biomed. Opt.  22, 60503–60504 (2017).

Heintzelman, D. L.

D. L. Heintzelman, U. Utzinger, H. Fuchs, A. Zuluaga, K. Gossage, A. M. Gillenwater, R. Jacob, B. Kemp, and R. R. Richards-Kortum, “Optimal excitation wavelengths for in vivo detection of oral neoplasia using fluorescence spectroscopy,” Photochem. Photobiol. 72(1), 103–113 (2000).
[Crossref] [PubMed]

Hinton, G.

Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521(7553), 436–444 (2015).
[Crossref] [PubMed]

N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, “Dropout: A Simple Way to Prevent Neural Networks from Overfitting,” J. Mach. Learn. Res. 15, 1929–1958 (2014).

Hurst, R. T.

N. Tajbakhsh, J. Y. Shin, S. R. Gurudu, R. T. Hurst, C. B. Kendall, M. B. Gotway, and Jianming Liang, “Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?” IEEE Trans. Med. Imaging 35(5), 1299–1312 (2016).
[Crossref] [PubMed]

Hutson, A. D.

V. Jayaprakash, M. Sullivan, M. Merzianu, N. R. Rigual, T. R. Loree, S. R. Popat, K. B. Moysich, S. Ramananda, T. Johnson, J. R. Marshall, A. D. Hutson, T. S. Mang, B. C. Wilson, S. R. Gill, J. Frustino, A. Bogaards, and M. E. Reid, “Autofluorescence-guided surveillance for oral cancer,” Cancer Prev. Res. 2(11), 966–974 (2009).
[Crossref] [PubMed]

Hwang, C. C.

S. W. Yang, Y. S. Lee, L. C. Chang, C. C. Hwang, and T. A. Chen, “Diagnostic significance of narrow-band imaging for detecting high-grade dysplasia, carcinoma in situ, and carcinoma in oral leukoplakia,” Laryngoscope 122(12), 2754–2761 (2012).
[Crossref] [PubMed]

Ingole, N.

M. S. Rahman, N. Ingole, D. Roblyer, V. Stepanek, R. Richards-Kortum, A. Gillenwater, S. Shastri, and P. Chaturvedi, “Evaluation of a low-cost, portable imaging system for early detection of oral cancer,” Head Neck Oncol. 2(1), 10 (2010).
[Crossref] [PubMed]

Jacob, R.

E. Svistun, R. Alizadeh-Naderi, A. El-Naggar, R. Jacob, A. Gillenwater, and R. Richards-Kortum, “Vision enhancement system for detection of oral cavity neoplasia based on autofluorescence,” Head Neck 26(3), 205–215 (2004).
[Crossref] [PubMed]

D. L. Heintzelman, U. Utzinger, H. Fuchs, A. Zuluaga, K. Gossage, A. M. Gillenwater, R. Jacob, B. Kemp, and R. R. Richards-Kortum, “Optimal excitation wavelengths for in vivo detection of oral neoplasia using fluorescence spectroscopy,” Photochem. Photobiol. 72(1), 103–113 (2000).
[Crossref] [PubMed]

A. Gillenwater, R. Jacob, R. Ganeshappa, B. Kemp, A. K. El-Naggar, J. L. Palmer, G. Clayman, M. F. Mitchell, and R. Richards-Kortum, “Noninvasive diagnosis of oral neoplasia based on fluorescence spectroscopy and native tissue autofluorescence,” Arch. Otolaryngol. Head Neck Surg. 124(11), 1251–1258 (1998).
[Crossref] [PubMed]

Jaremenko, C.

M. Aubreville, C. Knipfer, N. Oetter, C. Jaremenko, E. Rodner, J. Denzler, C. Bohr, H. Neumann, F. Stelzle, and A. Maier, “Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning,” Sci. Rep. 7(1), 11979 (2017).
[Crossref] [PubMed]

Jayaprakash, V.

V. Jayaprakash, M. Sullivan, M. Merzianu, N. R. Rigual, T. R. Loree, S. R. Popat, K. B. Moysich, S. Ramananda, T. Johnson, J. R. Marshall, A. D. Hutson, T. S. Mang, B. C. Wilson, S. R. Gill, J. Frustino, A. Bogaards, and M. E. Reid, “Autofluorescence-guided surveillance for oral cancer,” Cancer Prev. Res. 2(11), 966–974 (2009).
[Crossref] [PubMed]

Jemal, A.

K. D. Shield, J. Ferlay, A. Jemal, R. Sankaranarayanan, A. K. Chaturvedi, F. Bray, and I. Soerjomataram, “The global incidence of lip, oral cavity, and pharyngeal cancers by subsite in 2012,” CA Cancer J. Clin. 67(1), 51–64 (2017).
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Jena, S.

P. N. Birur, S. P. Sunny, S. Jena, U. Kandasarma, S. Raghavan, B. Ramaswamy, S. P. Shanmugam, S. Patrick, R. Kuriakose, J. Mallaiah, A. Suresh, R. Chigurupati, R. Desai, and M. A. Kuriakose, “Mobile health application for remote oral cancer surveillance,” J. Am. Dent. Assoc. 146(12), 886–894 (2015).
[Crossref] [PubMed]

Jianming Liang,

N. Tajbakhsh, J. Y. Shin, S. R. Gurudu, R. T. Hurst, C. B. Kendall, M. B. Gotway, and Jianming Liang, “Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?” IEEE Trans. Med. Imaging 35(5), 1299–1312 (2016).
[Crossref] [PubMed]

Johnson, T.

V. Jayaprakash, M. Sullivan, M. Merzianu, N. R. Rigual, T. R. Loree, S. R. Popat, K. B. Moysich, S. Ramananda, T. Johnson, J. R. Marshall, A. D. Hutson, T. S. Mang, B. C. Wilson, S. R. Gill, J. Frustino, A. Bogaards, and M. E. Reid, “Autofluorescence-guided surveillance for oral cancer,” Cancer Prev. Res. 2(11), 966–974 (2009).
[Crossref] [PubMed]

Kalwar, A.

M. K. Mallath, D. G. Taylor, R. A. Badwe, G. K. Rath, V. Shanta, C. S. Pramesh, R. Digumarti, P. Sebastian, B. B. Borthakur, A. Kalwar, S. Kapoor, S. Kumar, J. L. Gill, M. A. Kuriakose, H. Malhotra, S. C. Sharma, S. Shukla, L. Viswanath, R. T. Chacko, J. L. Pautu, K. S. Reddy, K. S. Sharma, A. D. Purushotham, and R. Sullivan, “The growing burden of cancer in India: epidemiology and social context,” Lancet Oncol. 15(6), e205–e212 (2014).
[Crossref] [PubMed]

Kandasarma, U.

P. N. Birur, S. P. Sunny, S. Jena, U. Kandasarma, S. Raghavan, B. Ramaswamy, S. P. Shanmugam, S. Patrick, R. Kuriakose, J. Mallaiah, A. Suresh, R. Chigurupati, R. Desai, and M. A. Kuriakose, “Mobile health application for remote oral cancer surveillance,” J. Am. Dent. Assoc. 146(12), 886–894 (2015).
[Crossref] [PubMed]

Kapoor, S.

M. K. Mallath, D. G. Taylor, R. A. Badwe, G. K. Rath, V. Shanta, C. S. Pramesh, R. Digumarti, P. Sebastian, B. B. Borthakur, A. Kalwar, S. Kapoor, S. Kumar, J. L. Gill, M. A. Kuriakose, H. Malhotra, S. C. Sharma, S. Shukla, L. Viswanath, R. T. Chacko, J. L. Pautu, K. S. Reddy, K. S. Sharma, A. D. Purushotham, and R. Sullivan, “The growing burden of cancer in India: epidemiology and social context,” Lancet Oncol. 15(6), e205–e212 (2014).
[Crossref] [PubMed]

Kemp, B.

D. L. Heintzelman, U. Utzinger, H. Fuchs, A. Zuluaga, K. Gossage, A. M. Gillenwater, R. Jacob, B. Kemp, and R. R. Richards-Kortum, “Optimal excitation wavelengths for in vivo detection of oral neoplasia using fluorescence spectroscopy,” Photochem. Photobiol. 72(1), 103–113 (2000).
[Crossref] [PubMed]

A. Gillenwater, R. Jacob, R. Ganeshappa, B. Kemp, A. K. El-Naggar, J. L. Palmer, G. Clayman, M. F. Mitchell, and R. Richards-Kortum, “Noninvasive diagnosis of oral neoplasia based on fluorescence spectroscopy and native tissue autofluorescence,” Arch. Otolaryngol. Head Neck Surg. 124(11), 1251–1258 (1998).
[Crossref] [PubMed]

Kendall, C. B.

N. Tajbakhsh, J. Y. Shin, S. R. Gurudu, R. T. Hurst, C. B. Kendall, M. B. Gotway, and Jianming Liang, “Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?” IEEE Trans. Med. Imaging 35(5), 1299–1312 (2016).
[Crossref] [PubMed]

Kim, R.

V. Gulshan, L. Peng, M. Coram, M. C. Stumpe, D. Wu, A. Narayanaswamy, S. Venugopalan, K. Widner, T. Madams, J. Cuadros, R. Kim, R. Raman, P. C. Nelson, J. L. Mega, and D. R. Webster, “Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs,” JAMA 316(22), 2402–2410 (2016).
[Crossref] [PubMed]

Knipfer, C.

M. Aubreville, C. Knipfer, N. Oetter, C. Jaremenko, E. Rodner, J. Denzler, C. Bohr, H. Neumann, F. Stelzle, and A. Maier, “Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning,” Sci. Rep. 7(1), 11979 (2017).
[Crossref] [PubMed]

Ko, J.

A. Esteva, B. Kuprel, R. A. Novoa, J. Ko, S. M. Swetter, H. M. Blau, and S. Thrun, “Dermatologist-level classification of skin cancer with deep neural networks,” Nature 542(7639), 115–118 (2017).
[Crossref] [PubMed]

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G. Litjens, T. Kooi, B. E. Bejnordi, A. A. A. Setio, F. Ciompi, M. Ghafoorian, J. A. W. M. van der Laak, B. van Ginneken, and C. I. Sánchez, “A survey on deep learning in medical image analysis,” Med. Image Anal. 42, 60–88 (2017).
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Krishnan, M. M. R.

M. M. R. Krishnan, V. Venkatraghavan, U. R. Acharya, M. Pal, R. R. Paul, L. C. Min, A. K. Ray, J. Chatterjee, and C. Chakraborty, “Automated oral cancer identification using histopathological images: a hybrid feature extraction paradigm,” Micron 43(2-3), 352–364 (2012).
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Krizhevsky, A.

N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, “Dropout: A Simple Way to Prevent Neural Networks from Overfitting,” J. Mach. Learn. Res. 15, 1929–1958 (2014).

Kuehle, M.

M. Rana, A. Zapf, M. Kuehle, N.-C. Gellrich, and A. M. Eckardt, “Clinical evaluation of an autofluorescence diagnostic device for oral cancer detection: a prospective randomized diagnostic study,” Eur. J. Cancer Prev. 21(5), 460–466 (2012).
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Kumar, S.

M. K. Mallath, D. G. Taylor, R. A. Badwe, G. K. Rath, V. Shanta, C. S. Pramesh, R. Digumarti, P. Sebastian, B. B. Borthakur, A. Kalwar, S. Kapoor, S. Kumar, J. L. Gill, M. A. Kuriakose, H. Malhotra, S. C. Sharma, S. Shukla, L. Viswanath, R. T. Chacko, J. L. Pautu, K. S. Reddy, K. S. Sharma, A. D. Purushotham, and R. Sullivan, “The growing burden of cancer in India: epidemiology and social context,” Lancet Oncol. 15(6), e205–e212 (2014).
[Crossref] [PubMed]

Kuprel, B.

A. Esteva, B. Kuprel, R. A. Novoa, J. Ko, S. M. Swetter, H. M. Blau, and S. Thrun, “Dermatologist-level classification of skin cancer with deep neural networks,” Nature 542(7639), 115–118 (2017).
[Crossref] [PubMed]

Kurachi, C.

D. Roblyer, C. Kurachi, V. Stepanek, M. D. Williams, A. K. El-Naggar, J. J. Lee, A. M. Gillenwater, and R. Richards-Kortum, “Objective detection and delineation of oral neoplasia using autofluorescence imaging,” Cancer Prev. Res. (Phila.) 2(5), 423–431 (2009).
[Crossref] [PubMed]

Kuriakose, M. A.

R. D. Uthoff, B. Song, P. Birur, M. A. Kuriakose, S. Sunny, A. Suresh, S. Patrick, A. Anbarani, O. Spires, P. Wilder-Smith, and R. Liang, “Development of a dual-modality, dual-view smartphone-based imaging system for oral cancer detection,” Proc. SPIE 10486, 104860V (2018).

P. N. Birur, S. P. Sunny, S. Jena, U. Kandasarma, S. Raghavan, B. Ramaswamy, S. P. Shanmugam, S. Patrick, R. Kuriakose, J. Mallaiah, A. Suresh, R. Chigurupati, R. Desai, and M. A. Kuriakose, “Mobile health application for remote oral cancer surveillance,” J. Am. Dent. Assoc. 146(12), 886–894 (2015).
[Crossref] [PubMed]

M. K. Mallath, D. G. Taylor, R. A. Badwe, G. K. Rath, V. Shanta, C. S. Pramesh, R. Digumarti, P. Sebastian, B. B. Borthakur, A. Kalwar, S. Kapoor, S. Kumar, J. L. Gill, M. A. Kuriakose, H. Malhotra, S. C. Sharma, S. Shukla, L. Viswanath, R. T. Chacko, J. L. Pautu, K. S. Reddy, K. S. Sharma, A. D. Purushotham, and R. Sullivan, “The growing burden of cancer in India: epidemiology and social context,” Lancet Oncol. 15(6), e205–e212 (2014).
[Crossref] [PubMed]

Kuriakose, R.

P. N. Birur, S. P. Sunny, S. Jena, U. Kandasarma, S. Raghavan, B. Ramaswamy, S. P. Shanmugam, S. Patrick, R. Kuriakose, J. Mallaiah, A. Suresh, R. Chigurupati, R. Desai, and M. A. Kuriakose, “Mobile health application for remote oral cancer surveillance,” J. Am. Dent. Assoc. 146(12), 886–894 (2015).
[Crossref] [PubMed]

Lane, P. M.

P. M. Lane, T. Gilhuly, P. D. Whitehead, H. Zeng, C. Poh, S. Ng, M. Williams, L. Zhang, M. Rosin, and C. E. MacAulay, “Simple device for the direct visualization of oral-cavity tissue fluorescence,” J. Biomed. Opt. 11, 24006–24007 (2006).

Le Campion, A. C. O. V.

A. C. O. V. Le Campion, C. M. B. Ribeiro, R. R. Luiz, F. F. da Silva Júnior, H. C. S. Barros, K. C. B. dos Santos, S. J. Ferreira, L. S. Gonçalves, and S. M. S. Ferreira, “Low survival rates of oral and oropharyngeal squamous cell carcinoma,” Int. J. Dent. 2017, 1–7 (2017).
[Crossref]

LeCun, Y.

Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521(7553), 436–444 (2015).
[Crossref] [PubMed]

Lee, J. J.

M. C. Pierce, R. A. Schwarz, V. S. Bhattar, S. Mondrik, M. D. Williams, J. J. Lee, R. Richards-Kortum, and A. M. Gillenwater, “Accuracy of in vivo multimodal optical imaging for detection of oral neoplasia,” Cancer Prev. Res. (Phila.) 5(6), 801–809 (2012).
[Crossref] [PubMed]

D. Roblyer, C. Kurachi, V. Stepanek, M. D. Williams, A. K. El-Naggar, J. J. Lee, A. M. Gillenwater, and R. Richards-Kortum, “Objective detection and delineation of oral neoplasia using autofluorescence imaging,” Cancer Prev. Res. (Phila.) 2(5), 423–431 (2009).
[Crossref] [PubMed]

Lee, Y.

R. Anantharaman, V. Anantharaman, and Y. Lee, “Oro Vision: Deep Learning for Classifying Orofacial Diseases,” in 2017 IEEE International Conference on Healthcare Informatics (ICHI) (2017), pp. 39–45.
[Crossref]

Lee, Y. S.

S. W. Yang, Y. S. Lee, L. C. Chang, C. C. Hwang, and T. A. Chen, “Diagnostic significance of narrow-band imaging for detecting high-grade dysplasia, carcinoma in situ, and carcinoma in oral leukoplakia,” Laryngoscope 122(12), 2754–2761 (2012).
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Li, K.

J. Deng, W. Dong, R. Socher, L. J. Li, K. Li, and L. Fei-Fei, “ImageNet: A large-scale hierarchical image database,” in 2009 IEEE Conference on Computer Vision and Pattern Recognition (2009), pp. 248–255.
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Li, L. J.

J. Deng, W. Dong, R. Socher, L. J. Li, K. Li, and L. Fei-Fei, “ImageNet: A large-scale hierarchical image database,” in 2009 IEEE Conference on Computer Vision and Pattern Recognition (2009), pp. 248–255.
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Liang, R.

R. D. Uthoff, B. Song, P. Birur, M. A. Kuriakose, S. Sunny, A. Suresh, S. Patrick, A. Anbarani, O. Spires, P. Wilder-Smith, and R. Liang, “Development of a dual-modality, dual-view smartphone-based imaging system for oral cancer detection,” Proc. SPIE 10486, 104860V (2018).

Litjens, G.

G. Litjens, T. Kooi, B. E. Bejnordi, A. A. A. Setio, F. Ciompi, M. Ghafoorian, J. A. W. M. van der Laak, B. van Ginneken, and C. I. Sánchez, “A survey on deep learning in medical image analysis,” Med. Image Anal. 42, 60–88 (2017).
[Crossref] [PubMed]

Little, J. V

M. Halicek, G. Lu, J. V Little, X. Wang, M. Patel, C. C. Griffith, M. W. El-Deiry, A. Y. Chen, and B. Fei, “Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging,” J. Biomed. Opt.  22, 60503–60504 (2017).

Loree, T. R.

V. Jayaprakash, M. Sullivan, M. Merzianu, N. R. Rigual, T. R. Loree, S. R. Popat, K. B. Moysich, S. Ramananda, T. Johnson, J. R. Marshall, A. D. Hutson, T. S. Mang, B. C. Wilson, S. R. Gill, J. Frustino, A. Bogaards, and M. E. Reid, “Autofluorescence-guided surveillance for oral cancer,” Cancer Prev. Res. 2(11), 966–974 (2009).
[Crossref] [PubMed]

Lu, G.

M. Halicek, G. Lu, J. V Little, X. Wang, M. Patel, C. C. Griffith, M. W. El-Deiry, A. Y. Chen, and B. Fei, “Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging,” J. Biomed. Opt.  22, 60503–60504 (2017).

Lu, L.

H. C. Shin, H. R. Roth, M. Gao, L. Lu, Z. Xu, I. Nogues, J. Yao, D. Mollura, and R. M. Summers, “Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning,” IEEE Trans. Med. Imaging 35(5), 1285–1298 (2016).
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A. C. O. V. Le Campion, C. M. B. Ribeiro, R. R. Luiz, F. F. da Silva Júnior, H. C. S. Barros, K. C. B. dos Santos, S. J. Ferreira, L. S. Gonçalves, and S. M. S. Ferreira, “Low survival rates of oral and oropharyngeal squamous cell carcinoma,” Int. J. Dent. 2017, 1–7 (2017).
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MacAulay, C. E.

C. F. Poh, C. E. MacAulay, L. Zhang, and M. P. Rosin, “Tracing the “At-Risk” Oral Mucosa Field with Autofluorescence: Steps Toward Clinical Impact,” Cancer Prev. Res. 2(5), 401–404 (2009)

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Madams, T.

V. Gulshan, L. Peng, M. Coram, M. C. Stumpe, D. Wu, A. Narayanaswamy, S. Venugopalan, K. Widner, T. Madams, J. Cuadros, R. Kim, R. Raman, P. C. Nelson, J. L. Mega, and D. R. Webster, “Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs,” JAMA 316(22), 2402–2410 (2016).
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M. Aubreville, C. Knipfer, N. Oetter, C. Jaremenko, E. Rodner, J. Denzler, C. Bohr, H. Neumann, F. Stelzle, and A. Maier, “Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning,” Sci. Rep. 7(1), 11979 (2017).
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Mallaiah, J.

P. N. Birur, S. P. Sunny, S. Jena, U. Kandasarma, S. Raghavan, B. Ramaswamy, S. P. Shanmugam, S. Patrick, R. Kuriakose, J. Mallaiah, A. Suresh, R. Chigurupati, R. Desai, and M. A. Kuriakose, “Mobile health application for remote oral cancer surveillance,” J. Am. Dent. Assoc. 146(12), 886–894 (2015).
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M. K. Mallath, D. G. Taylor, R. A. Badwe, G. K. Rath, V. Shanta, C. S. Pramesh, R. Digumarti, P. Sebastian, B. B. Borthakur, A. Kalwar, S. Kapoor, S. Kumar, J. L. Gill, M. A. Kuriakose, H. Malhotra, S. C. Sharma, S. Shukla, L. Viswanath, R. T. Chacko, J. L. Pautu, K. S. Reddy, K. S. Sharma, A. D. Purushotham, and R. Sullivan, “The growing burden of cancer in India: epidemiology and social context,” Lancet Oncol. 15(6), e205–e212 (2014).
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P. Mamoshina, A. Vieira, E. Putin, and A. Zhavoronkov, “Applications of Deep Learning in Biomedicine,” Mol. Pharm. 13(5), 1445–1454 (2016).
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R. Mehrotra, M. Singh, S. Thomas, P. Nair, S. Pandya, N. S. Nigam, and P. Shukla, “A cross-sectional study evaluating chemiluminescence and autofluorescence in the detection of clinically innocuous precancerous and cancerous oral lesions,” J. Am. Dent. Assoc. 141(2), 151–156 (2010).
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C. F. Poh, C. E. MacAulay, L. Zhang, and M. P. Rosin, “Tracing the “At-Risk” Oral Mucosa Field with Autofluorescence: Steps Toward Clinical Impact,” Cancer Prev. Res. 2(5), 401–404 (2009)

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P. Mamoshina, A. Vieira, E. Putin, and A. Zhavoronkov, “Applications of Deep Learning in Biomedicine,” Mol. Pharm. 13(5), 1445–1454 (2016).
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V. Jayaprakash, M. Sullivan, M. Merzianu, N. R. Rigual, T. R. Loree, S. R. Popat, K. B. Moysich, S. Ramananda, T. Johnson, J. R. Marshall, A. D. Hutson, T. S. Mang, B. C. Wilson, S. R. Gill, J. Frustino, A. Bogaards, and M. E. Reid, “Autofluorescence-guided surveillance for oral cancer,” Cancer Prev. Res. 2(11), 966–974 (2009).
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Ray, A. K.

M. M. R. Krishnan, V. Venkatraghavan, U. R. Acharya, M. Pal, R. R. Paul, L. C. Min, A. K. Ray, J. Chatterjee, and C. Chakraborty, “Automated oral cancer identification using histopathological images: a hybrid feature extraction paradigm,” Micron 43(2-3), 352–364 (2012).
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Reddy, K. S.

M. K. Mallath, D. G. Taylor, R. A. Badwe, G. K. Rath, V. Shanta, C. S. Pramesh, R. Digumarti, P. Sebastian, B. B. Borthakur, A. Kalwar, S. Kapoor, S. Kumar, J. L. Gill, M. A. Kuriakose, H. Malhotra, S. C. Sharma, S. Shukla, L. Viswanath, R. T. Chacko, J. L. Pautu, K. S. Reddy, K. S. Sharma, A. D. Purushotham, and R. Sullivan, “The growing burden of cancer in India: epidemiology and social context,” Lancet Oncol. 15(6), e205–e212 (2014).
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Reid, M. E.

V. Jayaprakash, M. Sullivan, M. Merzianu, N. R. Rigual, T. R. Loree, S. R. Popat, K. B. Moysich, S. Ramananda, T. Johnson, J. R. Marshall, A. D. Hutson, T. S. Mang, B. C. Wilson, S. R. Gill, J. Frustino, A. Bogaards, and M. E. Reid, “Autofluorescence-guided surveillance for oral cancer,” Cancer Prev. Res. 2(11), 966–974 (2009).
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M. C. Pierce, R. A. Schwarz, V. S. Bhattar, S. Mondrik, M. D. Williams, J. J. Lee, R. Richards-Kortum, and A. M. Gillenwater, “Accuracy of in vivo multimodal optical imaging for detection of oral neoplasia,” Cancer Prev. Res. (Phila.) 5(6), 801–809 (2012).
[Crossref] [PubMed]

M. S. Rahman, N. Ingole, D. Roblyer, V. Stepanek, R. Richards-Kortum, A. Gillenwater, S. Shastri, and P. Chaturvedi, “Evaluation of a low-cost, portable imaging system for early detection of oral cancer,” Head Neck Oncol. 2(1), 10 (2010).
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D. Roblyer, C. Kurachi, V. Stepanek, M. D. Williams, A. K. El-Naggar, J. J. Lee, A. M. Gillenwater, and R. Richards-Kortum, “Objective detection and delineation of oral neoplasia using autofluorescence imaging,” Cancer Prev. Res. (Phila.) 2(5), 423–431 (2009).
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I. Pavlova, M. Williams, A. El-Naggar, R. Richards-Kortum, and A. Gillenwater, “Understanding the Biological Basis of Autofluorescence Imaging for Oral Cancer Detection: High-Resolution Fluorescence Microscopy in Viable Tissue,” Clin. Cancer Res. 14(8), 2396–2404 (2008).

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P. N. Birur, S. P. Sunny, S. Jena, U. Kandasarma, S. Raghavan, B. Ramaswamy, S. P. Shanmugam, S. Patrick, R. Kuriakose, J. Mallaiah, A. Suresh, R. Chigurupati, R. Desai, and M. A. Kuriakose, “Mobile health application for remote oral cancer surveillance,” J. Am. Dent. Assoc. 146(12), 886–894 (2015).
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E. Svistun, R. Alizadeh-Naderi, A. El-Naggar, R. Jacob, A. Gillenwater, and R. Richards-Kortum, “Vision enhancement system for detection of oral cavity neoplasia based on autofluorescence,” Head Neck 26(3), 205–215 (2004).
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G. Litjens, T. Kooi, B. E. Bejnordi, A. A. A. Setio, F. Ciompi, M. Ghafoorian, J. A. W. M. van der Laak, B. van Ginneken, and C. I. Sánchez, “A survey on deep learning in medical image analysis,” Med. Image Anal. 42, 60–88 (2017).
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Webster, D. R.

V. Gulshan, L. Peng, M. Coram, M. C. Stumpe, D. Wu, A. Narayanaswamy, S. Venugopalan, K. Widner, T. Madams, J. Cuadros, R. Kim, R. Raman, P. C. Nelson, J. L. Mega, and D. R. Webster, “Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs,” JAMA 316(22), 2402–2410 (2016).
[Crossref] [PubMed]

Whitehead, P. D.

P. M. Lane, T. Gilhuly, P. D. Whitehead, H. Zeng, C. Poh, S. Ng, M. Williams, L. Zhang, M. Rosin, and C. E. MacAulay, “Simple device for the direct visualization of oral-cavity tissue fluorescence,” J. Biomed. Opt. 11, 24006–24007 (2006).

Widner, K.

V. Gulshan, L. Peng, M. Coram, M. C. Stumpe, D. Wu, A. Narayanaswamy, S. Venugopalan, K. Widner, T. Madams, J. Cuadros, R. Kim, R. Raman, P. C. Nelson, J. L. Mega, and D. R. Webster, “Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs,” JAMA 316(22), 2402–2410 (2016).
[Crossref] [PubMed]

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I. Pavlova, M. Williams, A. El-Naggar, R. Richards-Kortum, and A. Gillenwater, “Understanding the Biological Basis of Autofluorescence Imaging for Oral Cancer Detection: High-Resolution Fluorescence Microscopy in Viable Tissue,” Clin. Cancer Res. 14(8), 2396–2404 (2008).

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Williams, M. D.

M. C. Pierce, R. A. Schwarz, V. S. Bhattar, S. Mondrik, M. D. Williams, J. J. Lee, R. Richards-Kortum, and A. M. Gillenwater, “Accuracy of in vivo multimodal optical imaging for detection of oral neoplasia,” Cancer Prev. Res. (Phila.) 5(6), 801–809 (2012).
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Figures (7)

Fig. 1
Fig. 1 Low-cost, dual-modality smartphone-based oral cancer screening platform. The platform consists of a commercial LG G4 Android smartphone, an external peripheral with intraoral imaging attachment, LEDs, LED driver and batteries, a cloud-based image process and storage server. A custom Android application provides a user interface, controls the phone along with external peripherals, and enables communication with the cloud server and remote specialist.
Fig. 2
Fig. 2 Workflow of the proposed mobile imaging platform. Autofluorescence and white light images acquired from smartphone are uploaded to cloud server and classified for oral dysplasia and malignancy based on deep learning. Remote diagnosis could be provided by remote specialists anywhere with internet connections. Results can be viewed on-site through the customized mobile app.
Fig. 3
Fig. 3 Examples of dual-modal image pairs captured from the dual-modal mobile imaging device. (a) and (b) are autofluorescence image and white light image from the palate of a healthy patient, (c) and (d) are from the buccal mucosa of a patient with oral potentially malignant lesion, and (e) and (f) are image pairs of a malignant lesion from the lower vestibule.
Fig. 4
Fig. 4 Overview of the data preparation for dual-modal image classification. A new, three-channel data set is created from the autofluorescence and white light image pairs. The blue channel of the white light image which has low signal and high noise is excluded. The new three-channel image uses the green and red channels from the white light image and the normalized ratio of red and green channels from autofluorescence image as the third channel.
Fig. 5
Fig. 5 Data augmentation. Example of the data-augmented images. A total of 8 images are obtained from a single image by rotating and flipping the original image.
Fig. 6
Fig. 6 (a) The validation errors of three different neural network architectures: VGG-CNN-M, VGG-CNN-S, and VGG-16. VGG-CNN-M performs best among these three networks. (b) The comparison between the neural networks trained with and without augmented data. (c) The performances for different weight decays. (d) The performance with and without Dropout.
Fig. 7
Fig. 7 The performance of neural networks trained with dual-modal images, AFI, and WLI.

Tables (1)

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Table 1 Image data set used for developing deep learning image classification method.

Equations (1)

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E( w )= E 0 ( w )+ λ 2 i w i 2