Abstract

During pregnancy, the uterine cervix is the mechanical barrier that prevents delivery of a fetus. The underlying cervical collagen ultrastructure, which influences the overall mechanical properties of the cervix, plays a role in maintaining a successful pregnancy until term. Yet, not much is known about this collagen ultrastructure in pregnant and nonpregnant human tissue. We used optical coherence tomography to investigate the directionality and dispersion of collagen fiber bundles in the human cervix. An image analysis tool has been developed, combining a stitching method with a fiber orientation measurement, to study axially sliced cervix samples. This tool was used to analyze the ultrastructure of ex-vivo pregnant and non-pregnant hysterectomy tissue samples taken at the internal os, which is the region of the cervix adjacent to the uterus. With this tool, directionality maps of collagen fiber bundles and dispersion of collagen fiber orientation were analyzed. It was found that that the overall preferred directionality of the collagen fibers for both the nonpregnant and pregnant samples were circling around the inner cervical canal. Pregnant samples showed greater dispersion than non-pregnant samples. Lastly, we observed regional differences in collagen fiber dispersion. Fibers closer to the inner canal showed more dispersion than the fibers on the radial edges.

© 2015 Optical Society of America

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References

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2014 (5)

W. Yao, K. Yoshida, M. Fernandez, J. Vink, R. J. Wapner, C. V. Ananth, M. L. Oyen, and K. M. Myers, “Measuring the compressive viscoelastic mechanical properties of human cervical tissue using indentation,” J. Mech. Behav. Biomed. Mater. 34, 18–26 (2014).
[Crossref] [PubMed]

E. Mazza, M. Parra-Saavedra, M. Bajka, E. Gratacos, K. Nicolaides, and J. Deprest, “In vivo assessment of the biomechanical properties of the uterine cervix in pregnancy,” Prenat. Diagn. 34(1), 33–41 (2014).
[Crossref] [PubMed]

K. Yoshida, H. Jiang, M. Kim, J. Vink, S. Cremers, D. Paik, R. Wapner, M. Mahendroo, and K. Myers, “Quantitative Evaluation of Collagen Crosslinks and Corresponding Tensile Mechanical Properties in Mouse Cervical Tissue During Normal Pregnancy,” PLoS ONE 9(11), e112391 (2014).
[Crossref] [PubMed]

K. Yoshida, C. Reeves, J. Vink, J. Kitajewski, R. Wapner, H. Jiang, S. Cremers, and K. Myers, “Cervical Collagen Network Remodeling in Normal Pregnancy and Disrupted Parturition In Antxr2 Deficient mice,” J. Biomech. Eng. 136(2), 021017 (2014).
[Crossref] [PubMed]

K. L. Lurie, R. Angst, and A. K. Ellerbee, “Automated mosaicing of feature-poor optical coherence tomography volumes with an integrated white light imaging system,” IEEE Trans. Biomed. Eng. 61(7), 2141–2153 (2014).
[Crossref] [PubMed]

2013 (4)

2012 (2)

M. Mahendroo, “Cervical remodeling in term and preterm birth: insights from an animal model,” Reproduction 143(4), 429–438 (2012).
[Crossref] [PubMed]

H. Feltovich, T. J. Hall, and V. Berghella, “Beyond cervical length: emerging technologies for assessing the pregnant cervix,” Am. J. Obstet. Gynecol. 207(5), 345–354 (2012).
[Crossref] [PubMed]

2011 (4)

I. M. Orfanoudaki, D. Kappou, and S. Sifakis, “Recent advances in optical imaging for cervical cancer detection,” Arch. Gynecol. Obstet. 284(5), 1197–1208 (2011).
[Crossref] [PubMed]

W. Kang, X. Qi, N. J. Tresser, M. Kareta, J. L. Belinson, and A. M. Rollins, “Diagnostic efficacy of computer extracted image features in optical coherence tomography of the precancerous cervix,” Med. Phys. 38(1), 107–113 (2011).
[Crossref] [PubMed]

Y. Li, G. Gregori, B. L. Lam, and P. J. Rosenfeld, “Automatic montage of SD-OCT data sets,” Opt. Express 19(27), 26239–26248 (2011).
[Crossref] [PubMed]

J. Zheng, J. Tian, K. Deng, X. Dai, X. Zhang, and M. Xu, “Salient Feature Region: A New Method for Retinal Image Registration,” IEEE Trans. Inf. Technol. Biomed. 15(2), 221–232 (2011).
[Crossref] [PubMed]

2010 (3)

J. Chen, J. Tian, N. Lee, J. Zheng, R. T. Smith, and A. F. Laine, “A Partial Intensity Invariant Feature Descriptor for Multimodal Retinal Image Registration,” IEEE Trans. Biomed. Eng. 57(7), 1707–1718 (2010).
[Crossref] [PubMed]

B. Timmons, M. Akins, and M. Mahendroo, “Cervical remodeling during pregnancy and parturition,” Trends Endocrinol. Metab. 21(6), 353–361 (2010).
[Crossref] [PubMed]

K. M. Myers, S. Socrate, A. Paskaleva, and M. House, “A study of the anisotropy and tension/compression behavior of human cervical tissue,” J. Biomech. Eng. 132(2), 021003 (2010).
[Crossref] [PubMed]

2009 (3)

M. Emmenlauer, O. Ronneberger, A. Ponti, P. Schwarb, A. Griffa, A. Filippi, R. Nitschke, W. Driever, and H. Burkhardt, “XuvTools: free, fast and reliable stitching of large 3D datasets,” J. Microsc. 233(1), 42–60 (2009).
[Crossref] [PubMed]

K. Myers, S. Socrate, D. Tzeranis, and M. House, “Changes in the biochemical constituents and morphologic appearance of the human cervical stroma during pregnancy,” Eur. J. Obstet. Gynecol. Reprod. Biol. 144(Suppl 1), S82–S89 (2009).
[Crossref] [PubMed]

R. J. Zawadzki, S. S. Choi, A. R. Fuller, J. W. Evans, B. Hamann, and J. S. Werner, “Cellular resolution volumetric in vivo retinal imaging with adaptive optics-optical coherence tomography,” Opt. Express 17(5), 4084–4094 (2009).
[Crossref] [PubMed]

2008 (3)

C. P. Fleming, C. M. Ripplinger, B. Webb, I. R. Efimov, and A. M. Rollins, “Quantification of cardiac fiber orientation using optical coherence tomography,” J. Biomed. Opt. 13(3), 030505 (2008).
[Crossref] [PubMed]

K. M. Myers, A. P. Paskaleva, M. House, and S. Socrate, “Mechanical and biochemical properties of human cervical tissue,” Acta Biomater. 4(1), 104–116 (2008).
[Crossref] [PubMed]

S.-W. Lee, J.-Y. Yoo, J.-H. Kang, M.-S. Kang, S.-H. Jung, Y. Chong, D.-S. Cha, K.-H. Han, and B.-M. Kim, “Optical diagnosis of cervical intraepithelial neoplasm (CIN) using polarization-sensitive optical coherence tomography,” Opt. Express 16(4), 2709–2719 (2008).
[Crossref] [PubMed]

2006 (3)

S. Weiss, T. Jaermann, P. Schmid, P. Staempfli, P. Boesiger, P. Niederer, R. Caduff, and M. Bajka, “Three-dimensional fiber architecture of the nonpregnant human uterus determined ex vivo using magnetic resonance diffusion tensor imaging,” Anat. Rec. A Discov. Mol. Cell. Evol. Biol. 288(1), 84–90 (2006).
[Crossref] [PubMed]

E. Mazza, A. Nava, M. Bauer, R. Winter, M. Bajka, and G. A. Holzapfel, “Mechanical properties of the human uterine cervix: an in vivo study,” Med. Image Anal. 10(2), 125–136 (2006).
[Crossref] [PubMed]

N. Snavely, S. M. Seitz, and R. Szeliski, “Photo tourism: exploring photo collections in 3D,” ACM Trans. Graph. 25(3), 835–846 (2006).
[Crossref]

2004 (1)

D. G. Lowe, “Distinctive image features from scale-invariant keypoints,” Int. J. Comput. Vis. 60(2), 91–110 (2004).
[Crossref]

2003 (1)

R. A. Drezek, R. Richards-Kortum, M. A. Brewer, M. S. Feld, C. Pitris, A. Ferenczy, M. L. Faupel, and M. Follen, “Optical imaging of the cervix,” Cancer 98(S9), 2015–2027 (2003).
[Crossref] [PubMed]

1998 (1)

W. J. Karlon, J. W. Covell, A. D. McCulloch, J. J. Hunter, and J. H. Omens, “Automated measurement of myofiber disarray in transgenic mice with ventricular expression of ras,” Anat. Rec. 252(4), 612–625 (1998).
[Crossref] [PubMed]

1988 (1)

R. M. Aspden, “Collagen Organisation in the Cervix and its Relation to Mechanical Function,” Coll. Relat. Res. 8(2), 103–112 (1988).
[Crossref] [PubMed]

1983 (1)

P. J. Burt and E. H. Adelson, “A multiresolution spline with application to image mosaics,” ACM Trans. Graph. 2(4), 217–236 (1983).
[Crossref]

1959 (1)

E. W. Dijkstra, “A note on two problems in connexion with graphs,” Numerische Mathematik 1(1), 269–271 (1959).
[Crossref]

Adelson, E. H.

P. J. Burt and E. H. Adelson, “A multiresolution spline with application to image mosaics,” ACM Trans. Graph. 2(4), 217–236 (1983).
[Crossref]

Akins, M.

B. Timmons, M. Akins, and M. Mahendroo, “Cervical remodeling during pregnancy and parturition,” Trends Endocrinol. Metab. 21(6), 353–361 (2010).
[Crossref] [PubMed]

Ananth, C. V.

W. Yao, K. Yoshida, M. Fernandez, J. Vink, R. J. Wapner, C. V. Ananth, M. L. Oyen, and K. M. Myers, “Measuring the compressive viscoelastic mechanical properties of human cervical tissue using indentation,” J. Mech. Behav. Biomed. Mater. 34, 18–26 (2014).
[Crossref] [PubMed]

Angst, R.

K. L. Lurie, R. Angst, and A. K. Ellerbee, “Automated mosaicing of feature-poor optical coherence tomography volumes with an integrated white light imaging system,” IEEE Trans. Biomed. Eng. 61(7), 2141–2153 (2014).
[Crossref] [PubMed]

Aspden, R. M.

R. M. Aspden, “Collagen Organisation in the Cervix and its Relation to Mechanical Function,” Coll. Relat. Res. 8(2), 103–112 (1988).
[Crossref] [PubMed]

Badir, S.

S. Badir, M. Bajka, and E. Mazza, “A novel procedure for the mechanical characterization of the uterine cervix during pregnancy,” J. Mech. Behav. Biomed. Mater. 27, 143–153 (2013).
[Crossref] [PubMed]

Bajka, M.

E. Mazza, M. Parra-Saavedra, M. Bajka, E. Gratacos, K. Nicolaides, and J. Deprest, “In vivo assessment of the biomechanical properties of the uterine cervix in pregnancy,” Prenat. Diagn. 34(1), 33–41 (2014).
[Crossref] [PubMed]

S. Badir, M. Bajka, and E. Mazza, “A novel procedure for the mechanical characterization of the uterine cervix during pregnancy,” J. Mech. Behav. Biomed. Mater. 27, 143–153 (2013).
[Crossref] [PubMed]

E. Mazza, A. Nava, M. Bauer, R. Winter, M. Bajka, and G. A. Holzapfel, “Mechanical properties of the human uterine cervix: an in vivo study,” Med. Image Anal. 10(2), 125–136 (2006).
[Crossref] [PubMed]

S. Weiss, T. Jaermann, P. Schmid, P. Staempfli, P. Boesiger, P. Niederer, R. Caduff, and M. Bajka, “Three-dimensional fiber architecture of the nonpregnant human uterus determined ex vivo using magnetic resonance diffusion tensor imaging,” Anat. Rec. A Discov. Mol. Cell. Evol. Biol. 288(1), 84–90 (2006).
[Crossref] [PubMed]

Bauer, M.

E. Mazza, A. Nava, M. Bauer, R. Winter, M. Bajka, and G. A. Holzapfel, “Mechanical properties of the human uterine cervix: an in vivo study,” Med. Image Anal. 10(2), 125–136 (2006).
[Crossref] [PubMed]

Belinson, J. L.

W. Kang, X. Qi, N. J. Tresser, M. Kareta, J. L. Belinson, and A. M. Rollins, “Diagnostic efficacy of computer extracted image features in optical coherence tomography of the precancerous cervix,” Med. Phys. 38(1), 107–113 (2011).
[Crossref] [PubMed]

Berghella, V.

H. Feltovich, T. J. Hall, and V. Berghella, “Beyond cervical length: emerging technologies for assessing the pregnant cervix,” Am. J. Obstet. Gynecol. 207(5), 345–354 (2012).
[Crossref] [PubMed]

Boesiger, P.

S. Weiss, T. Jaermann, P. Schmid, P. Staempfli, P. Boesiger, P. Niederer, R. Caduff, and M. Bajka, “Three-dimensional fiber architecture of the nonpregnant human uterus determined ex vivo using magnetic resonance diffusion tensor imaging,” Anat. Rec. A Discov. Mol. Cell. Evol. Biol. 288(1), 84–90 (2006).
[Crossref] [PubMed]

Brewer, M. A.

R. A. Drezek, R. Richards-Kortum, M. A. Brewer, M. S. Feld, C. Pitris, A. Ferenczy, M. L. Faupel, and M. Follen, “Optical imaging of the cervix,” Cancer 98(S9), 2015–2027 (2003).
[Crossref] [PubMed]

Burkhardt, H.

M. Emmenlauer, O. Ronneberger, A. Ponti, P. Schwarb, A. Griffa, A. Filippi, R. Nitschke, W. Driever, and H. Burkhardt, “XuvTools: free, fast and reliable stitching of large 3D datasets,” J. Microsc. 233(1), 42–60 (2009).
[Crossref] [PubMed]

Burt, P. J.

P. J. Burt and E. H. Adelson, “A multiresolution spline with application to image mosaics,” ACM Trans. Graph. 2(4), 217–236 (1983).
[Crossref]

Caduff, R.

S. Weiss, T. Jaermann, P. Schmid, P. Staempfli, P. Boesiger, P. Niederer, R. Caduff, and M. Bajka, “Three-dimensional fiber architecture of the nonpregnant human uterus determined ex vivo using magnetic resonance diffusion tensor imaging,” Anat. Rec. A Discov. Mol. Cell. Evol. Biol. 288(1), 84–90 (2006).
[Crossref] [PubMed]

Cha, D.-S.

Chen, J.

J. Chen, J. Tian, N. Lee, J. Zheng, R. T. Smith, and A. F. Laine, “A Partial Intensity Invariant Feature Descriptor for Multimodal Retinal Image Registration,” IEEE Trans. Biomed. Eng. 57(7), 1707–1718 (2010).
[Crossref] [PubMed]

Chiu, S. J.

Choi, S. S.

Chong, Y.

Covell, J. W.

W. J. Karlon, J. W. Covell, A. D. McCulloch, J. J. Hunter, and J. H. Omens, “Automated measurement of myofiber disarray in transgenic mice with ventricular expression of ras,” Anat. Rec. 252(4), 612–625 (1998).
[Crossref] [PubMed]

Cremers, S.

K. Yoshida, H. Jiang, M. Kim, J. Vink, S. Cremers, D. Paik, R. Wapner, M. Mahendroo, and K. Myers, “Quantitative Evaluation of Collagen Crosslinks and Corresponding Tensile Mechanical Properties in Mouse Cervical Tissue During Normal Pregnancy,” PLoS ONE 9(11), e112391 (2014).
[Crossref] [PubMed]

K. Yoshida, C. Reeves, J. Vink, J. Kitajewski, R. Wapner, H. Jiang, S. Cremers, and K. Myers, “Cervical Collagen Network Remodeling in Normal Pregnancy and Disrupted Parturition In Antxr2 Deficient mice,” J. Biomech. Eng. 136(2), 021017 (2014).
[Crossref] [PubMed]

Dai, X.

J. Zheng, J. Tian, K. Deng, X. Dai, X. Zhang, and M. Xu, “Salient Feature Region: A New Method for Retinal Image Registration,” IEEE Trans. Inf. Technol. Biomed. 15(2), 221–232 (2011).
[Crossref] [PubMed]

Deng, K.

J. Zheng, J. Tian, K. Deng, X. Dai, X. Zhang, and M. Xu, “Salient Feature Region: A New Method for Retinal Image Registration,” IEEE Trans. Inf. Technol. Biomed. 15(2), 221–232 (2011).
[Crossref] [PubMed]

Deprest, J.

E. Mazza, M. Parra-Saavedra, M. Bajka, E. Gratacos, K. Nicolaides, and J. Deprest, “In vivo assessment of the biomechanical properties of the uterine cervix in pregnancy,” Prenat. Diagn. 34(1), 33–41 (2014).
[Crossref] [PubMed]

Dijkstra, E. W.

E. W. Dijkstra, “A note on two problems in connexion with graphs,” Numerische Mathematik 1(1), 269–271 (1959).
[Crossref]

Drezek, R. A.

R. A. Drezek, R. Richards-Kortum, M. A. Brewer, M. S. Feld, C. Pitris, A. Ferenczy, M. L. Faupel, and M. Follen, “Optical imaging of the cervix,” Cancer 98(S9), 2015–2027 (2003).
[Crossref] [PubMed]

Driever, W.

M. Emmenlauer, O. Ronneberger, A. Ponti, P. Schwarb, A. Griffa, A. Filippi, R. Nitschke, W. Driever, and H. Burkhardt, “XuvTools: free, fast and reliable stitching of large 3D datasets,” J. Microsc. 233(1), 42–60 (2009).
[Crossref] [PubMed]

Efimov, I. R.

C. P. Fleming, C. M. Ripplinger, B. Webb, I. R. Efimov, and A. M. Rollins, “Quantification of cardiac fiber orientation using optical coherence tomography,” J. Biomed. Opt. 13(3), 030505 (2008).
[Crossref] [PubMed]

Ellerbee, A. K.

K. L. Lurie, R. Angst, and A. K. Ellerbee, “Automated mosaicing of feature-poor optical coherence tomography volumes with an integrated white light imaging system,” IEEE Trans. Biomed. Eng. 61(7), 2141–2153 (2014).
[Crossref] [PubMed]

Emmenlauer, M.

M. Emmenlauer, O. Ronneberger, A. Ponti, P. Schwarb, A. Griffa, A. Filippi, R. Nitschke, W. Driever, and H. Burkhardt, “XuvTools: free, fast and reliable stitching of large 3D datasets,” J. Microsc. 233(1), 42–60 (2009).
[Crossref] [PubMed]

Estrada, R.

Evans, J. W.

Farsiu, S.

Faupel, M. L.

R. A. Drezek, R. Richards-Kortum, M. A. Brewer, M. S. Feld, C. Pitris, A. Ferenczy, M. L. Faupel, and M. Follen, “Optical imaging of the cervix,” Cancer 98(S9), 2015–2027 (2003).
[Crossref] [PubMed]

Feld, M. S.

R. A. Drezek, R. Richards-Kortum, M. A. Brewer, M. S. Feld, C. Pitris, A. Ferenczy, M. L. Faupel, and M. Follen, “Optical imaging of the cervix,” Cancer 98(S9), 2015–2027 (2003).
[Crossref] [PubMed]

Feltovich, H.

H. Feltovich, T. J. Hall, and V. Berghella, “Beyond cervical length: emerging technologies for assessing the pregnant cervix,” Am. J. Obstet. Gynecol. 207(5), 345–354 (2012).
[Crossref] [PubMed]

Ferenczy, A.

R. A. Drezek, R. Richards-Kortum, M. A. Brewer, M. S. Feld, C. Pitris, A. Ferenczy, M. L. Faupel, and M. Follen, “Optical imaging of the cervix,” Cancer 98(S9), 2015–2027 (2003).
[Crossref] [PubMed]

Fernandez, M.

W. Yao, K. Yoshida, M. Fernandez, J. Vink, R. J. Wapner, C. V. Ananth, M. L. Oyen, and K. M. Myers, “Measuring the compressive viscoelastic mechanical properties of human cervical tissue using indentation,” J. Mech. Behav. Biomed. Mater. 34, 18–26 (2014).
[Crossref] [PubMed]

M. Fernandez, J. Vink, K. Yoshida, R. Wapner, and K. M. Myers, “Direct measurement of the permeability of human cervical tissue,” J. Biomech. Eng. 135(2), 021024 (2013).
[Crossref] [PubMed]

Filippi, A.

M. Emmenlauer, O. Ronneberger, A. Ponti, P. Schwarb, A. Griffa, A. Filippi, R. Nitschke, W. Driever, and H. Burkhardt, “XuvTools: free, fast and reliable stitching of large 3D datasets,” J. Microsc. 233(1), 42–60 (2009).
[Crossref] [PubMed]

Fleming, C. P.

Y. Gan and C. P. Fleming, “Extracting three-dimensional orientation and tractography of myofibers using optical coherence tomography,” Biomed. Opt. Express 4(10), 2150–2165 (2013).
[Crossref] [PubMed]

C. P. Fleming, C. M. Ripplinger, B. Webb, I. R. Efimov, and A. M. Rollins, “Quantification of cardiac fiber orientation using optical coherence tomography,” J. Biomed. Opt. 13(3), 030505 (2008).
[Crossref] [PubMed]

Follen, M.

R. A. Drezek, R. Richards-Kortum, M. A. Brewer, M. S. Feld, C. Pitris, A. Ferenczy, M. L. Faupel, and M. Follen, “Optical imaging of the cervix,” Cancer 98(S9), 2015–2027 (2003).
[Crossref] [PubMed]

Fuller, A. R.

Gan, Y.

Gratacos, E.

E. Mazza, M. Parra-Saavedra, M. Bajka, E. Gratacos, K. Nicolaides, and J. Deprest, “In vivo assessment of the biomechanical properties of the uterine cervix in pregnancy,” Prenat. Diagn. 34(1), 33–41 (2014).
[Crossref] [PubMed]

Gregori, G.

Griffa, A.

M. Emmenlauer, O. Ronneberger, A. Ponti, P. Schwarb, A. Griffa, A. Filippi, R. Nitschke, W. Driever, and H. Burkhardt, “XuvTools: free, fast and reliable stitching of large 3D datasets,” J. Microsc. 233(1), 42–60 (2009).
[Crossref] [PubMed]

Hall, T. J.

H. Feltovich, T. J. Hall, and V. Berghella, “Beyond cervical length: emerging technologies for assessing the pregnant cervix,” Am. J. Obstet. Gynecol. 207(5), 345–354 (2012).
[Crossref] [PubMed]

Hamann, B.

Han, K.-H.

Hendargo, H. C.

Holzapfel, G. A.

E. Mazza, A. Nava, M. Bauer, R. Winter, M. Bajka, and G. A. Holzapfel, “Mechanical properties of the human uterine cervix: an in vivo study,” Med. Image Anal. 10(2), 125–136 (2006).
[Crossref] [PubMed]

House, M.

K. M. Myers, S. Socrate, A. Paskaleva, and M. House, “A study of the anisotropy and tension/compression behavior of human cervical tissue,” J. Biomech. Eng. 132(2), 021003 (2010).
[Crossref] [PubMed]

K. Myers, S. Socrate, D. Tzeranis, and M. House, “Changes in the biochemical constituents and morphologic appearance of the human cervical stroma during pregnancy,” Eur. J. Obstet. Gynecol. Reprod. Biol. 144(Suppl 1), S82–S89 (2009).
[Crossref] [PubMed]

K. M. Myers, A. P. Paskaleva, M. House, and S. Socrate, “Mechanical and biochemical properties of human cervical tissue,” Acta Biomater. 4(1), 104–116 (2008).
[Crossref] [PubMed]

Hunter, J. J.

W. J. Karlon, J. W. Covell, A. D. McCulloch, J. J. Hunter, and J. H. Omens, “Automated measurement of myofiber disarray in transgenic mice with ventricular expression of ras,” Anat. Rec. 252(4), 612–625 (1998).
[Crossref] [PubMed]

Izatt, J. A.

Jaermann, T.

S. Weiss, T. Jaermann, P. Schmid, P. Staempfli, P. Boesiger, P. Niederer, R. Caduff, and M. Bajka, “Three-dimensional fiber architecture of the nonpregnant human uterus determined ex vivo using magnetic resonance diffusion tensor imaging,” Anat. Rec. A Discov. Mol. Cell. Evol. Biol. 288(1), 84–90 (2006).
[Crossref] [PubMed]

Jiang, H.

K. Yoshida, C. Reeves, J. Vink, J. Kitajewski, R. Wapner, H. Jiang, S. Cremers, and K. Myers, “Cervical Collagen Network Remodeling in Normal Pregnancy and Disrupted Parturition In Antxr2 Deficient mice,” J. Biomech. Eng. 136(2), 021017 (2014).
[Crossref] [PubMed]

K. Yoshida, H. Jiang, M. Kim, J. Vink, S. Cremers, D. Paik, R. Wapner, M. Mahendroo, and K. Myers, “Quantitative Evaluation of Collagen Crosslinks and Corresponding Tensile Mechanical Properties in Mouse Cervical Tissue During Normal Pregnancy,” PLoS ONE 9(11), e112391 (2014).
[Crossref] [PubMed]

Jung, S.-H.

Kang, J.-H.

Kang, M.-S.

Kang, W.

W. Kang, X. Qi, N. J. Tresser, M. Kareta, J. L. Belinson, and A. M. Rollins, “Diagnostic efficacy of computer extracted image features in optical coherence tomography of the precancerous cervix,” Med. Phys. 38(1), 107–113 (2011).
[Crossref] [PubMed]

Kappou, D.

I. M. Orfanoudaki, D. Kappou, and S. Sifakis, “Recent advances in optical imaging for cervical cancer detection,” Arch. Gynecol. Obstet. 284(5), 1197–1208 (2011).
[Crossref] [PubMed]

Kareta, M.

W. Kang, X. Qi, N. J. Tresser, M. Kareta, J. L. Belinson, and A. M. Rollins, “Diagnostic efficacy of computer extracted image features in optical coherence tomography of the precancerous cervix,” Med. Phys. 38(1), 107–113 (2011).
[Crossref] [PubMed]

Karlon, W. J.

W. J. Karlon, J. W. Covell, A. D. McCulloch, J. J. Hunter, and J. H. Omens, “Automated measurement of myofiber disarray in transgenic mice with ventricular expression of ras,” Anat. Rec. 252(4), 612–625 (1998).
[Crossref] [PubMed]

Kim, B.-M.

Kim, M.

K. Yoshida, H. Jiang, M. Kim, J. Vink, S. Cremers, D. Paik, R. Wapner, M. Mahendroo, and K. Myers, “Quantitative Evaluation of Collagen Crosslinks and Corresponding Tensile Mechanical Properties in Mouse Cervical Tissue During Normal Pregnancy,” PLoS ONE 9(11), e112391 (2014).
[Crossref] [PubMed]

Kitajewski, J.

K. Yoshida, C. Reeves, J. Vink, J. Kitajewski, R. Wapner, H. Jiang, S. Cremers, and K. Myers, “Cervical Collagen Network Remodeling in Normal Pregnancy and Disrupted Parturition In Antxr2 Deficient mice,” J. Biomech. Eng. 136(2), 021017 (2014).
[Crossref] [PubMed]

Laine, A. F.

J. Chen, J. Tian, N. Lee, J. Zheng, R. T. Smith, and A. F. Laine, “A Partial Intensity Invariant Feature Descriptor for Multimodal Retinal Image Registration,” IEEE Trans. Biomed. Eng. 57(7), 1707–1718 (2010).
[Crossref] [PubMed]

Lam, B. L.

Lee, N.

J. Chen, J. Tian, N. Lee, J. Zheng, R. T. Smith, and A. F. Laine, “A Partial Intensity Invariant Feature Descriptor for Multimodal Retinal Image Registration,” IEEE Trans. Biomed. Eng. 57(7), 1707–1718 (2010).
[Crossref] [PubMed]

Lee, S.-W.

Li, Y.

Lowe, D. G.

D. G. Lowe, “Distinctive image features from scale-invariant keypoints,” Int. J. Comput. Vis. 60(2), 91–110 (2004).
[Crossref]

Lurie, K. L.

K. L. Lurie, R. Angst, and A. K. Ellerbee, “Automated mosaicing of feature-poor optical coherence tomography volumes with an integrated white light imaging system,” IEEE Trans. Biomed. Eng. 61(7), 2141–2153 (2014).
[Crossref] [PubMed]

Mahendroo, M.

K. Yoshida, H. Jiang, M. Kim, J. Vink, S. Cremers, D. Paik, R. Wapner, M. Mahendroo, and K. Myers, “Quantitative Evaluation of Collagen Crosslinks and Corresponding Tensile Mechanical Properties in Mouse Cervical Tissue During Normal Pregnancy,” PLoS ONE 9(11), e112391 (2014).
[Crossref] [PubMed]

M. Mahendroo, “Cervical remodeling in term and preterm birth: insights from an animal model,” Reproduction 143(4), 429–438 (2012).
[Crossref] [PubMed]

B. Timmons, M. Akins, and M. Mahendroo, “Cervical remodeling during pregnancy and parturition,” Trends Endocrinol. Metab. 21(6), 353–361 (2010).
[Crossref] [PubMed]

Mazza, E.

E. Mazza, M. Parra-Saavedra, M. Bajka, E. Gratacos, K. Nicolaides, and J. Deprest, “In vivo assessment of the biomechanical properties of the uterine cervix in pregnancy,” Prenat. Diagn. 34(1), 33–41 (2014).
[Crossref] [PubMed]

S. Badir, M. Bajka, and E. Mazza, “A novel procedure for the mechanical characterization of the uterine cervix during pregnancy,” J. Mech. Behav. Biomed. Mater. 27, 143–153 (2013).
[Crossref] [PubMed]

E. Mazza, A. Nava, M. Bauer, R. Winter, M. Bajka, and G. A. Holzapfel, “Mechanical properties of the human uterine cervix: an in vivo study,” Med. Image Anal. 10(2), 125–136 (2006).
[Crossref] [PubMed]

McCulloch, A. D.

W. J. Karlon, J. W. Covell, A. D. McCulloch, J. J. Hunter, and J. H. Omens, “Automated measurement of myofiber disarray in transgenic mice with ventricular expression of ras,” Anat. Rec. 252(4), 612–625 (1998).
[Crossref] [PubMed]

Myers, K.

K. Yoshida, H. Jiang, M. Kim, J. Vink, S. Cremers, D. Paik, R. Wapner, M. Mahendroo, and K. Myers, “Quantitative Evaluation of Collagen Crosslinks and Corresponding Tensile Mechanical Properties in Mouse Cervical Tissue During Normal Pregnancy,” PLoS ONE 9(11), e112391 (2014).
[Crossref] [PubMed]

K. Yoshida, C. Reeves, J. Vink, J. Kitajewski, R. Wapner, H. Jiang, S. Cremers, and K. Myers, “Cervical Collagen Network Remodeling in Normal Pregnancy and Disrupted Parturition In Antxr2 Deficient mice,” J. Biomech. Eng. 136(2), 021017 (2014).
[Crossref] [PubMed]

K. Myers, S. Socrate, D. Tzeranis, and M. House, “Changes in the biochemical constituents and morphologic appearance of the human cervical stroma during pregnancy,” Eur. J. Obstet. Gynecol. Reprod. Biol. 144(Suppl 1), S82–S89 (2009).
[Crossref] [PubMed]

Myers, K. M.

W. Yao, K. Yoshida, M. Fernandez, J. Vink, R. J. Wapner, C. V. Ananth, M. L. Oyen, and K. M. Myers, “Measuring the compressive viscoelastic mechanical properties of human cervical tissue using indentation,” J. Mech. Behav. Biomed. Mater. 34, 18–26 (2014).
[Crossref] [PubMed]

M. Fernandez, J. Vink, K. Yoshida, R. Wapner, and K. M. Myers, “Direct measurement of the permeability of human cervical tissue,” J. Biomech. Eng. 135(2), 021024 (2013).
[Crossref] [PubMed]

K. M. Myers, S. Socrate, A. Paskaleva, and M. House, “A study of the anisotropy and tension/compression behavior of human cervical tissue,” J. Biomech. Eng. 132(2), 021003 (2010).
[Crossref] [PubMed]

K. M. Myers, A. P. Paskaleva, M. House, and S. Socrate, “Mechanical and biochemical properties of human cervical tissue,” Acta Biomater. 4(1), 104–116 (2008).
[Crossref] [PubMed]

Nava, A.

E. Mazza, A. Nava, M. Bauer, R. Winter, M. Bajka, and G. A. Holzapfel, “Mechanical properties of the human uterine cervix: an in vivo study,” Med. Image Anal. 10(2), 125–136 (2006).
[Crossref] [PubMed]

Nicolaides, K.

E. Mazza, M. Parra-Saavedra, M. Bajka, E. Gratacos, K. Nicolaides, and J. Deprest, “In vivo assessment of the biomechanical properties of the uterine cervix in pregnancy,” Prenat. Diagn. 34(1), 33–41 (2014).
[Crossref] [PubMed]

Niederer, P.

S. Weiss, T. Jaermann, P. Schmid, P. Staempfli, P. Boesiger, P. Niederer, R. Caduff, and M. Bajka, “Three-dimensional fiber architecture of the nonpregnant human uterus determined ex vivo using magnetic resonance diffusion tensor imaging,” Anat. Rec. A Discov. Mol. Cell. Evol. Biol. 288(1), 84–90 (2006).
[Crossref] [PubMed]

Nitschke, R.

M. Emmenlauer, O. Ronneberger, A. Ponti, P. Schwarb, A. Griffa, A. Filippi, R. Nitschke, W. Driever, and H. Burkhardt, “XuvTools: free, fast and reliable stitching of large 3D datasets,” J. Microsc. 233(1), 42–60 (2009).
[Crossref] [PubMed]

Omens, J. H.

W. J. Karlon, J. W. Covell, A. D. McCulloch, J. J. Hunter, and J. H. Omens, “Automated measurement of myofiber disarray in transgenic mice with ventricular expression of ras,” Anat. Rec. 252(4), 612–625 (1998).
[Crossref] [PubMed]

Orfanoudaki, I. M.

I. M. Orfanoudaki, D. Kappou, and S. Sifakis, “Recent advances in optical imaging for cervical cancer detection,” Arch. Gynecol. Obstet. 284(5), 1197–1208 (2011).
[Crossref] [PubMed]

Oyen, M. L.

W. Yao, K. Yoshida, M. Fernandez, J. Vink, R. J. Wapner, C. V. Ananth, M. L. Oyen, and K. M. Myers, “Measuring the compressive viscoelastic mechanical properties of human cervical tissue using indentation,” J. Mech. Behav. Biomed. Mater. 34, 18–26 (2014).
[Crossref] [PubMed]

Paik, D.

K. Yoshida, H. Jiang, M. Kim, J. Vink, S. Cremers, D. Paik, R. Wapner, M. Mahendroo, and K. Myers, “Quantitative Evaluation of Collagen Crosslinks and Corresponding Tensile Mechanical Properties in Mouse Cervical Tissue During Normal Pregnancy,” PLoS ONE 9(11), e112391 (2014).
[Crossref] [PubMed]

Parra-Saavedra, M.

E. Mazza, M. Parra-Saavedra, M. Bajka, E. Gratacos, K. Nicolaides, and J. Deprest, “In vivo assessment of the biomechanical properties of the uterine cervix in pregnancy,” Prenat. Diagn. 34(1), 33–41 (2014).
[Crossref] [PubMed]

Paskaleva, A.

K. M. Myers, S. Socrate, A. Paskaleva, and M. House, “A study of the anisotropy and tension/compression behavior of human cervical tissue,” J. Biomech. Eng. 132(2), 021003 (2010).
[Crossref] [PubMed]

Paskaleva, A. P.

K. M. Myers, A. P. Paskaleva, M. House, and S. Socrate, “Mechanical and biochemical properties of human cervical tissue,” Acta Biomater. 4(1), 104–116 (2008).
[Crossref] [PubMed]

Pitris, C.

R. A. Drezek, R. Richards-Kortum, M. A. Brewer, M. S. Feld, C. Pitris, A. Ferenczy, M. L. Faupel, and M. Follen, “Optical imaging of the cervix,” Cancer 98(S9), 2015–2027 (2003).
[Crossref] [PubMed]

Ponti, A.

M. Emmenlauer, O. Ronneberger, A. Ponti, P. Schwarb, A. Griffa, A. Filippi, R. Nitschke, W. Driever, and H. Burkhardt, “XuvTools: free, fast and reliable stitching of large 3D datasets,” J. Microsc. 233(1), 42–60 (2009).
[Crossref] [PubMed]

Qi, X.

W. Kang, X. Qi, N. J. Tresser, M. Kareta, J. L. Belinson, and A. M. Rollins, “Diagnostic efficacy of computer extracted image features in optical coherence tomography of the precancerous cervix,” Med. Phys. 38(1), 107–113 (2011).
[Crossref] [PubMed]

Reeves, C.

K. Yoshida, C. Reeves, J. Vink, J. Kitajewski, R. Wapner, H. Jiang, S. Cremers, and K. Myers, “Cervical Collagen Network Remodeling in Normal Pregnancy and Disrupted Parturition In Antxr2 Deficient mice,” J. Biomech. Eng. 136(2), 021017 (2014).
[Crossref] [PubMed]

Richards-Kortum, R.

R. A. Drezek, R. Richards-Kortum, M. A. Brewer, M. S. Feld, C. Pitris, A. Ferenczy, M. L. Faupel, and M. Follen, “Optical imaging of the cervix,” Cancer 98(S9), 2015–2027 (2003).
[Crossref] [PubMed]

Ripplinger, C. M.

C. P. Fleming, C. M. Ripplinger, B. Webb, I. R. Efimov, and A. M. Rollins, “Quantification of cardiac fiber orientation using optical coherence tomography,” J. Biomed. Opt. 13(3), 030505 (2008).
[Crossref] [PubMed]

Rollins, A. M.

W. Kang, X. Qi, N. J. Tresser, M. Kareta, J. L. Belinson, and A. M. Rollins, “Diagnostic efficacy of computer extracted image features in optical coherence tomography of the precancerous cervix,” Med. Phys. 38(1), 107–113 (2011).
[Crossref] [PubMed]

C. P. Fleming, C. M. Ripplinger, B. Webb, I. R. Efimov, and A. M. Rollins, “Quantification of cardiac fiber orientation using optical coherence tomography,” J. Biomed. Opt. 13(3), 030505 (2008).
[Crossref] [PubMed]

Ronneberger, O.

M. Emmenlauer, O. Ronneberger, A. Ponti, P. Schwarb, A. Griffa, A. Filippi, R. Nitschke, W. Driever, and H. Burkhardt, “XuvTools: free, fast and reliable stitching of large 3D datasets,” J. Microsc. 233(1), 42–60 (2009).
[Crossref] [PubMed]

Rosenfeld, P. J.

Schmid, P.

S. Weiss, T. Jaermann, P. Schmid, P. Staempfli, P. Boesiger, P. Niederer, R. Caduff, and M. Bajka, “Three-dimensional fiber architecture of the nonpregnant human uterus determined ex vivo using magnetic resonance diffusion tensor imaging,” Anat. Rec. A Discov. Mol. Cell. Evol. Biol. 288(1), 84–90 (2006).
[Crossref] [PubMed]

Schwarb, P.

M. Emmenlauer, O. Ronneberger, A. Ponti, P. Schwarb, A. Griffa, A. Filippi, R. Nitschke, W. Driever, and H. Burkhardt, “XuvTools: free, fast and reliable stitching of large 3D datasets,” J. Microsc. 233(1), 42–60 (2009).
[Crossref] [PubMed]

Seitz, S. M.

N. Snavely, S. M. Seitz, and R. Szeliski, “Photo tourism: exploring photo collections in 3D,” ACM Trans. Graph. 25(3), 835–846 (2006).
[Crossref]

Sifakis, S.

I. M. Orfanoudaki, D. Kappou, and S. Sifakis, “Recent advances in optical imaging for cervical cancer detection,” Arch. Gynecol. Obstet. 284(5), 1197–1208 (2011).
[Crossref] [PubMed]

Smith, R. T.

J. Chen, J. Tian, N. Lee, J. Zheng, R. T. Smith, and A. F. Laine, “A Partial Intensity Invariant Feature Descriptor for Multimodal Retinal Image Registration,” IEEE Trans. Biomed. Eng. 57(7), 1707–1718 (2010).
[Crossref] [PubMed]

Snavely, N.

N. Snavely, S. M. Seitz, and R. Szeliski, “Photo tourism: exploring photo collections in 3D,” ACM Trans. Graph. 25(3), 835–846 (2006).
[Crossref]

Socrate, S.

K. M. Myers, S. Socrate, A. Paskaleva, and M. House, “A study of the anisotropy and tension/compression behavior of human cervical tissue,” J. Biomech. Eng. 132(2), 021003 (2010).
[Crossref] [PubMed]

K. Myers, S. Socrate, D. Tzeranis, and M. House, “Changes in the biochemical constituents and morphologic appearance of the human cervical stroma during pregnancy,” Eur. J. Obstet. Gynecol. Reprod. Biol. 144(Suppl 1), S82–S89 (2009).
[Crossref] [PubMed]

K. M. Myers, A. P. Paskaleva, M. House, and S. Socrate, “Mechanical and biochemical properties of human cervical tissue,” Acta Biomater. 4(1), 104–116 (2008).
[Crossref] [PubMed]

Staempfli, P.

S. Weiss, T. Jaermann, P. Schmid, P. Staempfli, P. Boesiger, P. Niederer, R. Caduff, and M. Bajka, “Three-dimensional fiber architecture of the nonpregnant human uterus determined ex vivo using magnetic resonance diffusion tensor imaging,” Anat. Rec. A Discov. Mol. Cell. Evol. Biol. 288(1), 84–90 (2006).
[Crossref] [PubMed]

Szeliski, R.

N. Snavely, S. M. Seitz, and R. Szeliski, “Photo tourism: exploring photo collections in 3D,” ACM Trans. Graph. 25(3), 835–846 (2006).
[Crossref]

Tian, J.

J. Zheng, J. Tian, K. Deng, X. Dai, X. Zhang, and M. Xu, “Salient Feature Region: A New Method for Retinal Image Registration,” IEEE Trans. Inf. Technol. Biomed. 15(2), 221–232 (2011).
[Crossref] [PubMed]

J. Chen, J. Tian, N. Lee, J. Zheng, R. T. Smith, and A. F. Laine, “A Partial Intensity Invariant Feature Descriptor for Multimodal Retinal Image Registration,” IEEE Trans. Biomed. Eng. 57(7), 1707–1718 (2010).
[Crossref] [PubMed]

Timmons, B.

B. Timmons, M. Akins, and M. Mahendroo, “Cervical remodeling during pregnancy and parturition,” Trends Endocrinol. Metab. 21(6), 353–361 (2010).
[Crossref] [PubMed]

Tomasi, C.

Tresser, N. J.

W. Kang, X. Qi, N. J. Tresser, M. Kareta, J. L. Belinson, and A. M. Rollins, “Diagnostic efficacy of computer extracted image features in optical coherence tomography of the precancerous cervix,” Med. Phys. 38(1), 107–113 (2011).
[Crossref] [PubMed]

Tzeranis, D.

K. Myers, S. Socrate, D. Tzeranis, and M. House, “Changes in the biochemical constituents and morphologic appearance of the human cervical stroma during pregnancy,” Eur. J. Obstet. Gynecol. Reprod. Biol. 144(Suppl 1), S82–S89 (2009).
[Crossref] [PubMed]

Vink, J.

K. Yoshida, C. Reeves, J. Vink, J. Kitajewski, R. Wapner, H. Jiang, S. Cremers, and K. Myers, “Cervical Collagen Network Remodeling in Normal Pregnancy and Disrupted Parturition In Antxr2 Deficient mice,” J. Biomech. Eng. 136(2), 021017 (2014).
[Crossref] [PubMed]

K. Yoshida, H. Jiang, M. Kim, J. Vink, S. Cremers, D. Paik, R. Wapner, M. Mahendroo, and K. Myers, “Quantitative Evaluation of Collagen Crosslinks and Corresponding Tensile Mechanical Properties in Mouse Cervical Tissue During Normal Pregnancy,” PLoS ONE 9(11), e112391 (2014).
[Crossref] [PubMed]

W. Yao, K. Yoshida, M. Fernandez, J. Vink, R. J. Wapner, C. V. Ananth, M. L. Oyen, and K. M. Myers, “Measuring the compressive viscoelastic mechanical properties of human cervical tissue using indentation,” J. Mech. Behav. Biomed. Mater. 34, 18–26 (2014).
[Crossref] [PubMed]

M. Fernandez, J. Vink, K. Yoshida, R. Wapner, and K. M. Myers, “Direct measurement of the permeability of human cervical tissue,” J. Biomech. Eng. 135(2), 021024 (2013).
[Crossref] [PubMed]

Wapner, R.

K. Yoshida, H. Jiang, M. Kim, J. Vink, S. Cremers, D. Paik, R. Wapner, M. Mahendroo, and K. Myers, “Quantitative Evaluation of Collagen Crosslinks and Corresponding Tensile Mechanical Properties in Mouse Cervical Tissue During Normal Pregnancy,” PLoS ONE 9(11), e112391 (2014).
[Crossref] [PubMed]

K. Yoshida, C. Reeves, J. Vink, J. Kitajewski, R. Wapner, H. Jiang, S. Cremers, and K. Myers, “Cervical Collagen Network Remodeling in Normal Pregnancy and Disrupted Parturition In Antxr2 Deficient mice,” J. Biomech. Eng. 136(2), 021017 (2014).
[Crossref] [PubMed]

M. Fernandez, J. Vink, K. Yoshida, R. Wapner, and K. M. Myers, “Direct measurement of the permeability of human cervical tissue,” J. Biomech. Eng. 135(2), 021024 (2013).
[Crossref] [PubMed]

Wapner, R. J.

W. Yao, K. Yoshida, M. Fernandez, J. Vink, R. J. Wapner, C. V. Ananth, M. L. Oyen, and K. M. Myers, “Measuring the compressive viscoelastic mechanical properties of human cervical tissue using indentation,” J. Mech. Behav. Biomed. Mater. 34, 18–26 (2014).
[Crossref] [PubMed]

Webb, B.

C. P. Fleming, C. M. Ripplinger, B. Webb, I. R. Efimov, and A. M. Rollins, “Quantification of cardiac fiber orientation using optical coherence tomography,” J. Biomed. Opt. 13(3), 030505 (2008).
[Crossref] [PubMed]

Weiss, S.

S. Weiss, T. Jaermann, P. Schmid, P. Staempfli, P. Boesiger, P. Niederer, R. Caduff, and M. Bajka, “Three-dimensional fiber architecture of the nonpregnant human uterus determined ex vivo using magnetic resonance diffusion tensor imaging,” Anat. Rec. A Discov. Mol. Cell. Evol. Biol. 288(1), 84–90 (2006).
[Crossref] [PubMed]

Werner, J. S.

Winter, R.

E. Mazza, A. Nava, M. Bauer, R. Winter, M. Bajka, and G. A. Holzapfel, “Mechanical properties of the human uterine cervix: an in vivo study,” Med. Image Anal. 10(2), 125–136 (2006).
[Crossref] [PubMed]

Xu, M.

J. Zheng, J. Tian, K. Deng, X. Dai, X. Zhang, and M. Xu, “Salient Feature Region: A New Method for Retinal Image Registration,” IEEE Trans. Inf. Technol. Biomed. 15(2), 221–232 (2011).
[Crossref] [PubMed]

Yao, W.

W. Yao, K. Yoshida, M. Fernandez, J. Vink, R. J. Wapner, C. V. Ananth, M. L. Oyen, and K. M. Myers, “Measuring the compressive viscoelastic mechanical properties of human cervical tissue using indentation,” J. Mech. Behav. Biomed. Mater. 34, 18–26 (2014).
[Crossref] [PubMed]

Yoo, J.-Y.

Yoshida, K.

W. Yao, K. Yoshida, M. Fernandez, J. Vink, R. J. Wapner, C. V. Ananth, M. L. Oyen, and K. M. Myers, “Measuring the compressive viscoelastic mechanical properties of human cervical tissue using indentation,” J. Mech. Behav. Biomed. Mater. 34, 18–26 (2014).
[Crossref] [PubMed]

K. Yoshida, C. Reeves, J. Vink, J. Kitajewski, R. Wapner, H. Jiang, S. Cremers, and K. Myers, “Cervical Collagen Network Remodeling in Normal Pregnancy and Disrupted Parturition In Antxr2 Deficient mice,” J. Biomech. Eng. 136(2), 021017 (2014).
[Crossref] [PubMed]

K. Yoshida, H. Jiang, M. Kim, J. Vink, S. Cremers, D. Paik, R. Wapner, M. Mahendroo, and K. Myers, “Quantitative Evaluation of Collagen Crosslinks and Corresponding Tensile Mechanical Properties in Mouse Cervical Tissue During Normal Pregnancy,” PLoS ONE 9(11), e112391 (2014).
[Crossref] [PubMed]

M. Fernandez, J. Vink, K. Yoshida, R. Wapner, and K. M. Myers, “Direct measurement of the permeability of human cervical tissue,” J. Biomech. Eng. 135(2), 021024 (2013).
[Crossref] [PubMed]

Zawadzki, R. J.

Zhang, X.

J. Zheng, J. Tian, K. Deng, X. Dai, X. Zhang, and M. Xu, “Salient Feature Region: A New Method for Retinal Image Registration,” IEEE Trans. Inf. Technol. Biomed. 15(2), 221–232 (2011).
[Crossref] [PubMed]

Zheng, J.

J. Zheng, J. Tian, K. Deng, X. Dai, X. Zhang, and M. Xu, “Salient Feature Region: A New Method for Retinal Image Registration,” IEEE Trans. Inf. Technol. Biomed. 15(2), 221–232 (2011).
[Crossref] [PubMed]

J. Chen, J. Tian, N. Lee, J. Zheng, R. T. Smith, and A. F. Laine, “A Partial Intensity Invariant Feature Descriptor for Multimodal Retinal Image Registration,” IEEE Trans. Biomed. Eng. 57(7), 1707–1718 (2010).
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N. Snavely, S. M. Seitz, and R. Szeliski, “Photo tourism: exploring photo collections in 3D,” ACM Trans. Graph. 25(3), 835–846 (2006).
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Acta Biomater. (1)

K. M. Myers, A. P. Paskaleva, M. House, and S. Socrate, “Mechanical and biochemical properties of human cervical tissue,” Acta Biomater. 4(1), 104–116 (2008).
[Crossref] [PubMed]

Am. J. Obstet. Gynecol. (1)

H. Feltovich, T. J. Hall, and V. Berghella, “Beyond cervical length: emerging technologies for assessing the pregnant cervix,” Am. J. Obstet. Gynecol. 207(5), 345–354 (2012).
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Anat. Rec. (1)

W. J. Karlon, J. W. Covell, A. D. McCulloch, J. J. Hunter, and J. H. Omens, “Automated measurement of myofiber disarray in transgenic mice with ventricular expression of ras,” Anat. Rec. 252(4), 612–625 (1998).
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S. Weiss, T. Jaermann, P. Schmid, P. Staempfli, P. Boesiger, P. Niederer, R. Caduff, and M. Bajka, “Three-dimensional fiber architecture of the nonpregnant human uterus determined ex vivo using magnetic resonance diffusion tensor imaging,” Anat. Rec. A Discov. Mol. Cell. Evol. Biol. 288(1), 84–90 (2006).
[Crossref] [PubMed]

Arch. Gynecol. Obstet. (1)

I. M. Orfanoudaki, D. Kappou, and S. Sifakis, “Recent advances in optical imaging for cervical cancer detection,” Arch. Gynecol. Obstet. 284(5), 1197–1208 (2011).
[Crossref] [PubMed]

Biomed. Opt. Express (2)

Cancer (1)

R. A. Drezek, R. Richards-Kortum, M. A. Brewer, M. S. Feld, C. Pitris, A. Ferenczy, M. L. Faupel, and M. Follen, “Optical imaging of the cervix,” Cancer 98(S9), 2015–2027 (2003).
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R. M. Aspden, “Collagen Organisation in the Cervix and its Relation to Mechanical Function,” Coll. Relat. Res. 8(2), 103–112 (1988).
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Eur. J. Obstet. Gynecol. Reprod. Biol. (1)

K. Myers, S. Socrate, D. Tzeranis, and M. House, “Changes in the biochemical constituents and morphologic appearance of the human cervical stroma during pregnancy,” Eur. J. Obstet. Gynecol. Reprod. Biol. 144(Suppl 1), S82–S89 (2009).
[Crossref] [PubMed]

IEEE Trans. Biomed. Eng. (2)

K. L. Lurie, R. Angst, and A. K. Ellerbee, “Automated mosaicing of feature-poor optical coherence tomography volumes with an integrated white light imaging system,” IEEE Trans. Biomed. Eng. 61(7), 2141–2153 (2014).
[Crossref] [PubMed]

J. Chen, J. Tian, N. Lee, J. Zheng, R. T. Smith, and A. F. Laine, “A Partial Intensity Invariant Feature Descriptor for Multimodal Retinal Image Registration,” IEEE Trans. Biomed. Eng. 57(7), 1707–1718 (2010).
[Crossref] [PubMed]

IEEE Trans. Inf. Technol. Biomed. (1)

J. Zheng, J. Tian, K. Deng, X. Dai, X. Zhang, and M. Xu, “Salient Feature Region: A New Method for Retinal Image Registration,” IEEE Trans. Inf. Technol. Biomed. 15(2), 221–232 (2011).
[Crossref] [PubMed]

Int. J. Comput. Vis. (1)

D. G. Lowe, “Distinctive image features from scale-invariant keypoints,” Int. J. Comput. Vis. 60(2), 91–110 (2004).
[Crossref]

J. Biomech. Eng. (3)

K. Yoshida, C. Reeves, J. Vink, J. Kitajewski, R. Wapner, H. Jiang, S. Cremers, and K. Myers, “Cervical Collagen Network Remodeling in Normal Pregnancy and Disrupted Parturition In Antxr2 Deficient mice,” J. Biomech. Eng. 136(2), 021017 (2014).
[Crossref] [PubMed]

K. M. Myers, S. Socrate, A. Paskaleva, and M. House, “A study of the anisotropy and tension/compression behavior of human cervical tissue,” J. Biomech. Eng. 132(2), 021003 (2010).
[Crossref] [PubMed]

M. Fernandez, J. Vink, K. Yoshida, R. Wapner, and K. M. Myers, “Direct measurement of the permeability of human cervical tissue,” J. Biomech. Eng. 135(2), 021024 (2013).
[Crossref] [PubMed]

J. Biomed. Opt. (1)

C. P. Fleming, C. M. Ripplinger, B. Webb, I. R. Efimov, and A. M. Rollins, “Quantification of cardiac fiber orientation using optical coherence tomography,” J. Biomed. Opt. 13(3), 030505 (2008).
[Crossref] [PubMed]

J. Mech. Behav. Biomed. Mater. (2)

S. Badir, M. Bajka, and E. Mazza, “A novel procedure for the mechanical characterization of the uterine cervix during pregnancy,” J. Mech. Behav. Biomed. Mater. 27, 143–153 (2013).
[Crossref] [PubMed]

W. Yao, K. Yoshida, M. Fernandez, J. Vink, R. J. Wapner, C. V. Ananth, M. L. Oyen, and K. M. Myers, “Measuring the compressive viscoelastic mechanical properties of human cervical tissue using indentation,” J. Mech. Behav. Biomed. Mater. 34, 18–26 (2014).
[Crossref] [PubMed]

J. Microsc. (1)

M. Emmenlauer, O. Ronneberger, A. Ponti, P. Schwarb, A. Griffa, A. Filippi, R. Nitschke, W. Driever, and H. Burkhardt, “XuvTools: free, fast and reliable stitching of large 3D datasets,” J. Microsc. 233(1), 42–60 (2009).
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Med. Image Anal. (1)

E. Mazza, A. Nava, M. Bauer, R. Winter, M. Bajka, and G. A. Holzapfel, “Mechanical properties of the human uterine cervix: an in vivo study,” Med. Image Anal. 10(2), 125–136 (2006).
[Crossref] [PubMed]

Med. Phys. (1)

W. Kang, X. Qi, N. J. Tresser, M. Kareta, J. L. Belinson, and A. M. Rollins, “Diagnostic efficacy of computer extracted image features in optical coherence tomography of the precancerous cervix,” Med. Phys. 38(1), 107–113 (2011).
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Opt. Express (3)

PLoS ONE (1)

K. Yoshida, H. Jiang, M. Kim, J. Vink, S. Cremers, D. Paik, R. Wapner, M. Mahendroo, and K. Myers, “Quantitative Evaluation of Collagen Crosslinks and Corresponding Tensile Mechanical Properties in Mouse Cervical Tissue During Normal Pregnancy,” PLoS ONE 9(11), e112391 (2014).
[Crossref] [PubMed]

Prenat. Diagn. (1)

E. Mazza, M. Parra-Saavedra, M. Bajka, E. Gratacos, K. Nicolaides, and J. Deprest, “In vivo assessment of the biomechanical properties of the uterine cervix in pregnancy,” Prenat. Diagn. 34(1), 33–41 (2014).
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B. Timmons, M. Akins, and M. Mahendroo, “Cervical remodeling during pregnancy and parturition,” Trends Endocrinol. Metab. 21(6), 353–361 (2010).
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Other (5)

M. Niemeijer, M. K. Garvin, K. Lee, B. van Ginneken, M. D. Abràmoff, and M. Sonka, “Registration of 3D spectral OCT volumes using 3D SIFT feature point matching,” in SPIE Medical Imaging, (International Society for Optics and Photonics, 2009), 72591I–72591I–72598.

M. Fernandez, M. House, S. Jambawalikar, J. Vink, R. Wapner, and K. Myers, “Investigating the Mechanical Function of the Cervix during Pregnancy using Finite Element Models derived from High Resolution 3D MRI,” Submitted to Comput Methods Biomech Biomed Engin (2014).

A. G. Capps, R. J. Zawadzki, J. S. Werner, and B. Hamann, “Combined volume registration and visualization,” in Visualization in Medicine and Life Sciences, (The Eurographics Association, 2013), 7–11.

P. Cattin, H. Bay, L. Van Gool, and G. Székely, “Retina Mosaicing Using Local Features,” in Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006, R. Larsen, M. Nielsen, and J. Sporring, eds. (Springer Berlin Heidelberg, 2006), pp. 185–192.

K. Myers, C. Hendon, Y. Gan, W. Yao, J. Vink, and R. Wapner, “A Continuous Fiber Distribution Material Model for Human Cervical Tissue,” in press, Journal of Biomechanics Special Issue of Reproductive Biomechanics (2015).

Supplementary Material (2)

» Media 1: AVI (8888 KB)     
» Media 2: AVI (14867 KB)     

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Figures (10)

Fig. 1
Fig. 1 Flowchart of the registration algorithm. Scale invariant transform (SIFT) is used in pair matching within the en face plane. Calibration along z-axis is based on estimation in first block and edge detection results. Linear regression models are used and least square estimations are calculated in global registration within en face plane and along the z directions. An error auto-correction method was used to detect and eliminate the unreliable estimation in pairwise estimation. After all offset are calculated, we use gain compensation and multiband blending method to reduce the artifacts which are caused by the inconsistent intensity among multiple volumes in the overlapped area.
Fig. 2
Fig. 2 Schematics of registration (a) in three dimensions; (b) within the en face plane of the camera image; (c) overlapped area in 3D; (d) overlapped B-scans. Within en face plane, the offsets between two volumes are measured through keypoint matching in (b). Here, only keypoints that are matched are shown. There are hundreds of keypoints in the camera image. The number of extracted keypoints and ratio of matched features vary with camera images and overlapped areas. According to our experiment, only a small proportion (~5%) of keypoints can be matched. The centroids of multiple volumes are estimated globally by considering their offsets. To register the OCT volumes along the z-axis, the B-scans at the overlapped area are compared in (d). The displacement of the detected edge shows the offset along the z-axis among volumes.
Fig. 3
Fig. 3 Schematics of error auto-correction within the en face plane. Each node denotes an OCT volume within the en face plane. Each link represents a pairwise offset estimation based on SIFT. The links are color coded based on the error between pairwise offset estimation and global optimization, e (i,j). Blue color indicates that the error is within 1 pixel, and red indicates that the error is over 1 pixel. The pruning process is shown from (a) to (c). The initial structure is in (a). After a deletion of 8 nodes, only a small number of erroneous links exist in (b). The most reliable tree is established after deleting 17 nodes as shown in (c). The spanning process is shown from (c) to (e). Nodes are added at each iteration. Only reliable links are added to the tree structure at each iteration. Therefore, the structure of (d) is more reliable than that of (b), though the two figures share the same number of nodes. The constructed tree is shown in (e). With pruning and spanning, we delete the erroneous links and construct an offset tree with highly reliable links.
Fig. 4
Fig. 4 Schematics of post processing in two dimensions. For all input images, the overlapped region is calculated. Then a gain factor for each volume is computed based on the intensity of overlapped region. The intensity of each volume is tuned by the gain factor. Each B-scan is divided into multiple bands. The banded images are weighted with different matrix based on the idea of blending low frequency band with larger range and blending high frequency band with smaller range. The reconstructed image is the weighted summation of all bands.
Fig. 5
Fig. 5 Measured maximum error between pairwise offset estimation and global optimization during (a) pruning and (b) spanning process. The x-axis in (a) is in decreased numbers. The curve between 51 to 37 is zoomed in the inserted figure. In pruning, the measured maximum error drops with number of nodes in global estimation. Through link selection, the maximum error remains unaltered with additions of new nodes.
Fig. 6
Fig. 6 Comparison of (a) four stitched volumes and (b) the whole volumes. Four volumes with sizes of 2.5 mm × 2.5 mm × 2.51 mm were imaged and stitched using our algorithm in (a). Within the same space, another OCT volume with a size of 4 mm × 4 mm × 2.51 mm was acquired for comparison. Eight landmarks were specified in each volume, formatting four pairs of distances. The distances were measured and compared in voxel as a validation of the accuracy of stitching algorithm. The maximum mismatch in the two volumes does not exceed 15 voxels.
Fig. 7
Fig. 7 Registration results within the en face plane (a) with and (b) without the error correction. Registration of B-scan results from (c) hard combination of multiple B-scans, (d) gain compensation of multiple B-scans, and (e) gain compensation plus multiband blending of multiple B-scans. The volumes are not stitched properly without error correction in (a). After error correction, the volumes are well arranged within the en face place with a consistent contour of the cervix. In a zoomed area indicated by dashed yellow rectangle, if hard combined, the two sections approximating the edge have great difference in pixel value in (c1). Gain compensation uniformed the pixel value but a boundary is still visible in (d1). When proceeding with multiband blending, a smooth transition of pixel values is visible over the edge in (e1).
Fig. 8
Fig. 8 Registered results of (a-d) PG and (e-l) NP samples. In particular, (a, c, e, f, i, k) are stitched camera image in two dimensions while (b, d, f, h, j, l) are stitched OCT volumes. For one PG sample, 53 volumes are stitched as a new volume of 30 mm × 27 mm × 7 mm. For another PG sample, 54 volumes are stitched as a new volume of 28 mm × 27 mm × 4 mm. We stitched 40 volumes for the first NP sample and formed a whole volume of 20 mm × 24 mm × 5 mm. We stitched 41 volumes for the second NP sample and formed a whole volume of 21 mm × 26 mm × 5 mm. We stitched 24 volumes for the third NP sample and formed a whole volume of 15 mm × 19 mm × 5 mm. We stitched 48 volumes for the fourth NP sample and formed a whole volume of 24 mm × 31 mm × 5 mm. Smooth surfaces are observed when multiple volumes are combined.
Fig. 9
Fig. 9 Representative OCT images of (a-d) PG and (e-l) PG cervix. The FOV are 30 mm × 27 mm in (a)-(b), 28 mm × 27 mm in (c)-(d), 20 mm × 24 mm in (e-f), 21 mm × 26 mm in (g)-(h), 19 mm × 15 mm in (i)-(j), 24 mm × 31 mm in (k)-(l) . The image is a 2D plane that is parallel to the surface with a vertical depth of 245 μm. Fiber orientation results were processed for each OCT image. The estimations of orientation were made on each 1000 μm x 1000 μm. The results are color-coded based on confidence value. Two typical results are shown at 10 depths below 245 μm with an increment of 49 μm in Media 1 and Media 2 for a PG(a-b) sample and a NP(e-f) sample. The fiber orientation does not vary much within the range of depths.
Fig. 10
Fig. 10 Distribution over 12 sub-regions (a) – (l) of non-pregnant (NP) (red) and pregnant (PG) (blue) samples. For each sub-region with a size of 1000 μm x 1000 μm area, the distribution is averaged over 10 depth with an increment of 49 μm. From (a) to (l), the peak value of distribution in NP is higher than the value in PG, which indicates less dispersion and more regularity.

Tables (3)

Tables Icon

Table 1 Algorithm 1. Pruning process. Starting from all nodes, the algorithm progressively eliminates the node that causes largest error. The nodes in the list of good nodes construct the most reliable tree structure with all pairwise links at high accuracy.

Tables Icon

Table 2 Algorithm 2. Spanning process. Starting from the list of good nodes, the algorithm iteratively adds nodes and links from the list of bad nodes. When one node is added, every newly constructed link is examined. Links that cause large error are eliminated.

Tables Icon

Table 1 Statistic of the confidence value at inner region (e, f, d, l), middle region (c, d, i, j), and outer region (a, b, g, h). The confidence value is measured as mean ± standard deviation.

Equations (20)

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D i s d e s = { a cos ( d e s d e s k ) | k D E S j }
Dx i j = median ( { x i k x j k } k = 1 K )
Dy i j = median ( { y i k y j k } k = 1 K )
W c = d
m t h r o w : [ 0 1 0 0 -1 0 0 0 0 0 0 0 ] ( m + M ) t h r o w : [ 0 0 0 0 0 0 0 1 0 0 -1 0 ]
c ^ = ( W T W ) 1 W T d
e ( i , j ) = | e p ( i , j ) e g ( i , j ) |
V z = d 2
z ^ = ( V T V ) 1 V T d 2
E = 1 2 i = 1 n j = 1 n N i j ( ( g i I i j g j I j i ) 2 / σ N 2 + ( 1 g i ) 2 / σ g 2 )
( 2 σ N 2 j = 1 n I i j 2 N i j 1 σ g 2 j = 1 n N i j ) g i j = 1 n 2 N i j I i j I j i σ N 2 g j = 1 σ g 2 j = 1 n N i j
W max n ( i , j ) = { 1 , i f W n ( i , j ) = arg max j { W n ( i , j ) } 0 , o t h e r w i s e
I ( k + 1 ) σ n = I k σ n * g σ '
B ( k + 1 ) σ n = I k σ n I ( k + 1 ) σ n
W ( k + 1 ) σ n = W k σ n * g σ '
G ( i , j ) = G x 2 ( i , j ) + G y 2 ( i , j )
Φ ( i , j ) = a tan ( G y / G x )
P ( ω ) W = P ˜ ( ω ) W / ω = 0 179 P ˜ ( ω ) W
P ˜ ( ω ) W = ( i , j ) W G ( i , j ) exp ( 2 cos [ 2 ( ω Φ ( i , j ) ) ] ) exp ( 2 )
c = P ( ω ¯ ) σ

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