Abstract

Automated image segmentation is a critical step toward achieving a quantitative evaluation of disease states with imaging techniques. Two-photon fluorescence microscopy (TPM) has been employed to visualize the retinal pigmented epithelium (RPE) and provide images indicating the health of the retina. However, segmentation of RPE cells within TPM images is difficult due to small differences in fluorescence intensity between cell borders and cell bodies. Here we present a semi-automated method for segmenting RPE cells that relies upon multiple weak features that differentiate cell borders from the remaining image. These features were scored by a search optimization procedure that built up the cell border in segments around a nucleus of interest. With six images used as a test, our method correctly identified cell borders for 69% of nuclei on average. Performance was strongly dependent upon increasing retinosome content in the RPE. TPM image analysis has the potential of providing improved early quantitative assessments of diseases affecting the RPE.

© 2015 Optical Society of America

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References

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2014 (3)

G. Palczewska, Z. Dong, M. Golczak, J. J. Hunter, D. R. Williams, N. S. Alexander, and K. Palczewski, “Noninvasive two-photon microscopy imaging of mouse retina and retinal pigment epithelium through the pupil of the eye,” Nat. Med. 20(7), 785–789 (2014).
[Crossref] [PubMed]

H. Wu, X. Geng, X. Zhang, M. Qiu, K. Jiang, L. Tang, and J. Dong, “A self-adaptive distance regularized level set evolution method for optical disk segmentation,” Biomed. Mater. Eng. 24(6), 3199–3206 (2014).
[PubMed]

A. Maeda, G. Palczewska, M. Golczak, H. Kohno, Z. Dong, T. Maeda, and K. Palczewski, “Two-photon microscopy reveals early rod photoreceptor cell damage in light-exposed mutant mice,” Proc. Natl. Acad. Sci. U.S.A. 111(14), E1428–E1437 (2014).
[Crossref] [PubMed]

2013 (4)

2012 (2)

2011 (2)

A. A. Dima, J. T. Elliott, J. J. Filliben, M. Halter, A. Peskin, J. Bernal, M. Kociolek, M. C. Brady, H. C. Tang, and A. L. Plant, “Comparison of segmentation algorithms for fluorescence microscopy images of cells,” Cytometry A 79(7), 545–559 (2011).
[Crossref] [PubMed]

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

2009 (1)

R. Kolár, R. Laemmer, J. Jan, and ChY. Mardin, “The segmentation of zones with increased autofluorescence in the junctional zone of parapapillary atrophy,” Physiol. Meas. 30(5), 505–516 (2009).
[Crossref] [PubMed]

2007 (2)

A. Roorda, Y. Zhang, and J. L. Duncan, “High-resolution in vivo imaging of the RPE mosaic in eyes with retinal disease,” Invest. Ophthalmol. Vis. Sci. 48(5), 2297–2303 (2007).
[Crossref] [PubMed]

A. A. Hill, P. LaPan, Y. Li, and S. Haney, “Impact of image segmentation on high-content screening data quality for SK-BR-3 cells,” BMC Bioinformatics 8(1), 340 (2007).
[Crossref] [PubMed]

2004 (2)

N. M. Bressler, “Age-related macular degeneration is the leading cause of blindness,” JAMA 291(15), 1900–1901 (2004).
[Crossref] [PubMed]

Y. Imanishi, M. L. Batten, D. W. Piston, W. Baehr, and K. Palczewski, “Noninvasive two-photon imaging reveals retinyl ester storage structures in the eye,” J. Cell Biol. 164(3), 373–383 (2004).
[Crossref] [PubMed]

1986 (1)

J. Kittler and J. Illingworth, “Minimum error thresholding,” Pattern Recognit. 19(1), 41–47 (1986).
[Crossref]

Ahnelt, P.

K. Bredies, M. Wagner, C. Schubert, and P. Ahnelt, “Computer-assisted counting of retinal cells by automatic segmentation after TV denoising,” BMC Ophthalmol. 13(1), 59 (2013).
[Crossref] [PubMed]

Alexander, N. S.

G. Palczewska, Z. Dong, M. Golczak, J. J. Hunter, D. R. Williams, N. S. Alexander, and K. Palczewski, “Noninvasive two-photon microscopy imaging of mouse retina and retinal pigment epithelium through the pupil of the eye,” Nat. Med. 20(7), 785–789 (2014).
[Crossref] [PubMed]

Baehr, W.

Y. Imanishi, M. L. Batten, D. W. Piston, W. Baehr, and K. Palczewski, “Noninvasive two-photon imaging reveals retinyl ester storage structures in the eye,” J. Cell Biol. 164(3), 373–383 (2004).
[Crossref] [PubMed]

Batten, M. L.

Y. Imanishi, M. L. Batten, D. W. Piston, W. Baehr, and K. Palczewski, “Noninvasive two-photon imaging reveals retinyl ester storage structures in the eye,” J. Cell Biol. 164(3), 373–383 (2004).
[Crossref] [PubMed]

Bernal, J.

A. A. Dima, J. T. Elliott, J. J. Filliben, M. Halter, A. Peskin, J. Bernal, M. Kociolek, M. C. Brady, H. C. Tang, and A. L. Plant, “Comparison of segmentation algorithms for fluorescence microscopy images of cells,” Cytometry A 79(7), 545–559 (2011).
[Crossref] [PubMed]

Bollini, S. S.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Bowes Rickman, C.

Brady, M. C.

A. A. Dima, J. T. Elliott, J. J. Filliben, M. Halter, A. Peskin, J. Bernal, M. Kociolek, M. C. Brady, H. C. Tang, and A. L. Plant, “Comparison of segmentation algorithms for fluorescence microscopy images of cells,” Cytometry A 79(7), 545–559 (2011).
[Crossref] [PubMed]

Bredies, K.

K. Bredies, M. Wagner, C. Schubert, and P. Ahnelt, “Computer-assisted counting of retinal cells by automatic segmentation after TV denoising,” BMC Ophthalmol. 13(1), 59 (2013).
[Crossref] [PubMed]

Bressler, N. M.

N. M. Bressler, “Age-related macular degeneration is the leading cause of blindness,” JAMA 291(15), 1900–1901 (2004).
[Crossref] [PubMed]

Carroll, J.

Chiu, S. J.

Dhillon, B.

T. B. Tang, C. K. Lu, A. Laude, B. Dhillon, and A. F. Murray, “Noise reduction for ellipse fitting on medical images,” Electron. Lett. 49(3), 178–179 (2013).
[Crossref]

Dilley, J.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Dima, A. A.

A. A. Dima, J. T. Elliott, J. J. Filliben, M. Halter, A. Peskin, J. Bernal, M. Kociolek, M. C. Brady, H. C. Tang, and A. L. Plant, “Comparison of segmentation algorithms for fluorescence microscopy images of cells,” Cytometry A 79(7), 545–559 (2011).
[Crossref] [PubMed]

Ding, J.-D.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Dong, J.

H. Wu, X. Geng, X. Zhang, M. Qiu, K. Jiang, L. Tang, and J. Dong, “A self-adaptive distance regularized level set evolution method for optical disk segmentation,” Biomed. Mater. Eng. 24(6), 3199–3206 (2014).
[PubMed]

Dong, Z.

A. Maeda, G. Palczewska, M. Golczak, H. Kohno, Z. Dong, T. Maeda, and K. Palczewski, “Two-photon microscopy reveals early rod photoreceptor cell damage in light-exposed mutant mice,” Proc. Natl. Acad. Sci. U.S.A. 111(14), E1428–E1437 (2014).
[Crossref] [PubMed]

G. Palczewska, Z. Dong, M. Golczak, J. J. Hunter, D. R. Williams, N. S. Alexander, and K. Palczewski, “Noninvasive two-photon microscopy imaging of mouse retina and retinal pigment epithelium through the pupil of the eye,” Nat. Med. 20(7), 785–789 (2014).
[Crossref] [PubMed]

Dubis, A. M.

Dubra, A.

Duncan, J. L.

A. Roorda, Y. Zhang, and J. L. Duncan, “High-resolution in vivo imaging of the RPE mosaic in eyes with retinal disease,” Invest. Ophthalmol. Vis. Sci. 48(5), 2297–2303 (2007).
[Crossref] [PubMed]

Elliott, J. T.

A. A. Dima, J. T. Elliott, J. J. Filliben, M. Halter, A. Peskin, J. Bernal, M. Kociolek, M. C. Brady, H. C. Tang, and A. L. Plant, “Comparison of segmentation algorithms for fluorescence microscopy images of cells,” Cytometry A 79(7), 545–559 (2011).
[Crossref] [PubMed]

Farsiu, S.

S. J. Chiu, Y. Lokhnygina, A. M. Dubis, A. Dubra, J. Carroll, J. A. Izatt, and S. Farsiu, “Automatic cone photoreceptor segmentation using graph theory and dynamic programming,” Biomed. Opt. Express 4(6), 924–937 (2013).
[Crossref] [PubMed]

S. J. Chiu, C. A. Toth, C. Bowes Rickman, J. A. Izatt, and S. Farsiu, “Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming,” Biomed. Opt. Express 3(5), 1127–1140 (2012).
[Crossref] [PubMed]

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Filliben, J. J.

A. A. Dima, J. T. Elliott, J. J. Filliben, M. Halter, A. Peskin, J. Bernal, M. Kociolek, M. C. Brady, H. C. Tang, and A. L. Plant, “Comparison of segmentation algorithms for fluorescence microscopy images of cells,” Cytometry A 79(7), 545–559 (2011).
[Crossref] [PubMed]

Geng, X.

H. Wu, X. Geng, X. Zhang, M. Qiu, K. Jiang, L. Tang, and J. Dong, “A self-adaptive distance regularized level set evolution method for optical disk segmentation,” Biomed. Mater. Eng. 24(6), 3199–3206 (2014).
[PubMed]

Golczak, M.

A. Maeda, G. Palczewska, M. Golczak, H. Kohno, Z. Dong, T. Maeda, and K. Palczewski, “Two-photon microscopy reveals early rod photoreceptor cell damage in light-exposed mutant mice,” Proc. Natl. Acad. Sci. U.S.A. 111(14), E1428–E1437 (2014).
[Crossref] [PubMed]

G. Palczewska, Z. Dong, M. Golczak, J. J. Hunter, D. R. Williams, N. S. Alexander, and K. Palczewski, “Noninvasive two-photon microscopy imaging of mouse retina and retinal pigment epithelium through the pupil of the eye,” Nat. Med. 20(7), 785–789 (2014).
[Crossref] [PubMed]

Gómez-Vieyra, A.

Groelle, M.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Halter, M.

A. A. Dima, J. T. Elliott, J. J. Filliben, M. Halter, A. Peskin, J. Bernal, M. Kociolek, M. C. Brady, H. C. Tang, and A. L. Plant, “Comparison of segmentation algorithms for fluorescence microscopy images of cells,” Cytometry A 79(7), 545–559 (2011).
[Crossref] [PubMed]

Haney, S.

A. A. Hill, P. LaPan, Y. Li, and S. Haney, “Impact of image segmentation on high-content screening data quality for SK-BR-3 cells,” BMC Bioinformatics 8(1), 340 (2007).
[Crossref] [PubMed]

Harrabi, O.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Herrmann, R.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Hill, A. A.

A. A. Hill, P. LaPan, Y. Li, and S. Haney, “Impact of image segmentation on high-content screening data quality for SK-BR-3 cells,” BMC Bioinformatics 8(1), 340 (2007).
[Crossref] [PubMed]

Hunter, J. J.

G. Palczewska, Z. Dong, M. Golczak, J. J. Hunter, D. R. Williams, N. S. Alexander, and K. Palczewski, “Noninvasive two-photon microscopy imaging of mouse retina and retinal pigment epithelium through the pupil of the eye,” Nat. Med. 20(7), 785–789 (2014).
[Crossref] [PubMed]

Illingworth, J.

J. Kittler and J. Illingworth, “Minimum error thresholding,” Pattern Recognit. 19(1), 41–47 (1986).
[Crossref]

Imanishi, Y.

Y. Imanishi, M. L. Batten, D. W. Piston, W. Baehr, and K. Palczewski, “Noninvasive two-photon imaging reveals retinyl ester storage structures in the eye,” J. Cell Biol. 164(3), 373–383 (2004).
[Crossref] [PubMed]

Izatt, J. A.

Jamison, J. A.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Jan, J.

R. Kolár, R. Laemmer, J. Jan, and ChY. Mardin, “The segmentation of zones with increased autofluorescence in the junctional zone of parapapillary atrophy,” Physiol. Meas. 30(5), 505–516 (2009).
[Crossref] [PubMed]

Jiang, K.

H. Wu, X. Geng, X. Zhang, M. Qiu, K. Jiang, L. Tang, and J. Dong, “A self-adaptive distance regularized level set evolution method for optical disk segmentation,” Biomed. Mater. Eng. 24(6), 3199–3206 (2014).
[PubMed]

Johnson, L. V.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Kelly, U.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Kittler, J.

J. Kittler and J. Illingworth, “Minimum error thresholding,” Pattern Recognit. 19(1), 41–47 (1986).
[Crossref]

Kobayashi, D.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Kociolek, M.

A. A. Dima, J. T. Elliott, J. J. Filliben, M. Halter, A. Peskin, J. Bernal, M. Kociolek, M. C. Brady, H. C. Tang, and A. L. Plant, “Comparison of segmentation algorithms for fluorescence microscopy images of cells,” Cytometry A 79(7), 545–559 (2011).
[Crossref] [PubMed]

Kohno, H.

A. Maeda, G. Palczewska, M. Golczak, H. Kohno, Z. Dong, T. Maeda, and K. Palczewski, “Two-photon microscopy reveals early rod photoreceptor cell damage in light-exposed mutant mice,” Proc. Natl. Acad. Sci. U.S.A. 111(14), E1428–E1437 (2014).
[Crossref] [PubMed]

Kolár, R.

R. Kolár, R. Laemmer, J. Jan, and ChY. Mardin, “The segmentation of zones with increased autofluorescence in the junctional zone of parapapillary atrophy,” Physiol. Meas. 30(5), 505–516 (2009).
[Crossref] [PubMed]

Kuang, B.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Laemmer, R.

R. Kolár, R. Laemmer, J. Jan, and ChY. Mardin, “The segmentation of zones with increased autofluorescence in the junctional zone of parapapillary atrophy,” Physiol. Meas. 30(5), 505–516 (2009).
[Crossref] [PubMed]

LaPan, P.

A. A. Hill, P. LaPan, Y. Li, and S. Haney, “Impact of image segmentation on high-content screening data quality for SK-BR-3 cells,” BMC Bioinformatics 8(1), 340 (2007).
[Crossref] [PubMed]

Laude, A.

T. B. Tang, C. K. Lu, A. Laude, B. Dhillon, and A. F. Murray, “Noise reduction for ellipse fitting on medical images,” Electron. Lett. 49(3), 178–179 (2013).
[Crossref]

Li, W.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Li, Y.

A. A. Hill, P. LaPan, Y. Li, and S. Haney, “Impact of image segmentation on high-content screening data quality for SK-BR-3 cells,” BMC Bioinformatics 8(1), 340 (2007).
[Crossref] [PubMed]

Lin, J. C.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Lokhnygina, Y.

Lu, C. K.

T. B. Tang, C. K. Lu, A. Laude, B. Dhillon, and A. F. Murray, “Noise reduction for ellipse fitting on medical images,” Electron. Lett. 49(3), 178–179 (2013).
[Crossref]

Mace, B. E.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Maeda, A.

A. Maeda, G. Palczewska, M. Golczak, H. Kohno, Z. Dong, T. Maeda, and K. Palczewski, “Two-photon microscopy reveals early rod photoreceptor cell damage in light-exposed mutant mice,” Proc. Natl. Acad. Sci. U.S.A. 111(14), E1428–E1437 (2014).
[Crossref] [PubMed]

Maeda, T.

A. Maeda, G. Palczewska, M. Golczak, H. Kohno, Z. Dong, T. Maeda, and K. Palczewski, “Two-photon microscopy reveals early rod photoreceptor cell damage in light-exposed mutant mice,” Proc. Natl. Acad. Sci. U.S.A. 111(14), E1428–E1437 (2014).
[Crossref] [PubMed]

Malacara-Hernández, D.

Mardin, ChY.

R. Kolár, R. Laemmer, J. Jan, and ChY. Mardin, “The segmentation of zones with increased autofluorescence in the junctional zone of parapapillary atrophy,” Physiol. Meas. 30(5), 505–516 (2009).
[Crossref] [PubMed]

Meijering, E.

E. Meijering, “Cell Segmentation: 50 Years Down the Road,” IEEE Signal Process. Mag. 29(5), 140–145 (2012).
[Crossref]

Murray, A. F.

T. B. Tang, C. K. Lu, A. Laude, B. Dhillon, and A. F. Murray, “Noise reduction for ellipse fitting on medical images,” Electron. Lett. 49(3), 178–179 (2013).
[Crossref]

Palczewska, G.

A. Maeda, G. Palczewska, M. Golczak, H. Kohno, Z. Dong, T. Maeda, and K. Palczewski, “Two-photon microscopy reveals early rod photoreceptor cell damage in light-exposed mutant mice,” Proc. Natl. Acad. Sci. U.S.A. 111(14), E1428–E1437 (2014).
[Crossref] [PubMed]

G. Palczewska, Z. Dong, M. Golczak, J. J. Hunter, D. R. Williams, N. S. Alexander, and K. Palczewski, “Noninvasive two-photon microscopy imaging of mouse retina and retinal pigment epithelium through the pupil of the eye,” Nat. Med. 20(7), 785–789 (2014).
[Crossref] [PubMed]

Palczewski, K.

G. Palczewska, Z. Dong, M. Golczak, J. J. Hunter, D. R. Williams, N. S. Alexander, and K. Palczewski, “Noninvasive two-photon microscopy imaging of mouse retina and retinal pigment epithelium through the pupil of the eye,” Nat. Med. 20(7), 785–789 (2014).
[Crossref] [PubMed]

A. Maeda, G. Palczewska, M. Golczak, H. Kohno, Z. Dong, T. Maeda, and K. Palczewski, “Two-photon microscopy reveals early rod photoreceptor cell damage in light-exposed mutant mice,” Proc. Natl. Acad. Sci. U.S.A. 111(14), E1428–E1437 (2014).
[Crossref] [PubMed]

Y. Imanishi, M. L. Batten, D. W. Piston, W. Baehr, and K. Palczewski, “Noninvasive two-photon imaging reveals retinyl ester storage structures in the eye,” J. Cell Biol. 164(3), 373–383 (2004).
[Crossref] [PubMed]

Peskin, A.

A. A. Dima, J. T. Elliott, J. J. Filliben, M. Halter, A. Peskin, J. Bernal, M. Kociolek, M. C. Brady, H. C. Tang, and A. L. Plant, “Comparison of segmentation algorithms for fluorescence microscopy images of cells,” Cytometry A 79(7), 545–559 (2011).
[Crossref] [PubMed]

Piston, D. W.

Y. Imanishi, M. L. Batten, D. W. Piston, W. Baehr, and K. Palczewski, “Noninvasive two-photon imaging reveals retinyl ester storage structures in the eye,” J. Cell Biol. 164(3), 373–383 (2004).
[Crossref] [PubMed]

Plant, A. L.

A. A. Dima, J. T. Elliott, J. J. Filliben, M. Halter, A. Peskin, J. Bernal, M. Kociolek, M. C. Brady, H. C. Tang, and A. L. Plant, “Comparison of segmentation algorithms for fluorescence microscopy images of cells,” Cytometry A 79(7), 545–559 (2011).
[Crossref] [PubMed]

Pons, J.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Qiu, M.

H. Wu, X. Geng, X. Zhang, M. Qiu, K. Jiang, L. Tang, and J. Dong, “A self-adaptive distance regularized level set evolution method for optical disk segmentation,” Biomed. Mater. Eng. 24(6), 3199–3206 (2014).
[PubMed]

Rangel-Fonseca, P.

Rickman, C.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Roorda, A.

A. Roorda, Y. Zhang, and J. L. Duncan, “High-resolution in vivo imaging of the RPE mosaic in eyes with retinal disease,” Invest. Ophthalmol. Vis. Sci. 48(5), 2297–2303 (2007).
[Crossref] [PubMed]

Rossi, E. A.

Schubert, C.

K. Bredies, M. Wagner, C. Schubert, and P. Ahnelt, “Computer-assisted counting of retinal cells by automatic segmentation after TV denoising,” BMC Ophthalmol. 13(1), 59 (2013).
[Crossref] [PubMed]

Smith, S. G.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Sullivan, P.

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

Tang, H. C.

A. A. Dima, J. T. Elliott, J. J. Filliben, M. Halter, A. Peskin, J. Bernal, M. Kociolek, M. C. Brady, H. C. Tang, and A. L. Plant, “Comparison of segmentation algorithms for fluorescence microscopy images of cells,” Cytometry A 79(7), 545–559 (2011).
[Crossref] [PubMed]

Tang, L.

H. Wu, X. Geng, X. Zhang, M. Qiu, K. Jiang, L. Tang, and J. Dong, “A self-adaptive distance regularized level set evolution method for optical disk segmentation,” Biomed. Mater. Eng. 24(6), 3199–3206 (2014).
[PubMed]

Tang, T. B.

T. B. Tang, C. K. Lu, A. Laude, B. Dhillon, and A. F. Murray, “Noise reduction for ellipse fitting on medical images,” Electron. Lett. 49(3), 178–179 (2013).
[Crossref]

Toth, C. A.

Wagner, M.

K. Bredies, M. Wagner, C. Schubert, and P. Ahnelt, “Computer-assisted counting of retinal cells by automatic segmentation after TV denoising,” BMC Ophthalmol. 13(1), 59 (2013).
[Crossref] [PubMed]

Williams, D. R.

G. Palczewska, Z. Dong, M. Golczak, J. J. Hunter, D. R. Williams, N. S. Alexander, and K. Palczewski, “Noninvasive two-photon microscopy imaging of mouse retina and retinal pigment epithelium through the pupil of the eye,” Nat. Med. 20(7), 785–789 (2014).
[Crossref] [PubMed]

P. Rangel-Fonseca, A. Gómez-Vieyra, D. Malacara-Hernández, M. C. Wilson, D. R. Williams, and E. A. Rossi, “Automated segmentation of retinal pigment epithelium cells in fluorescence adaptive optics images,” J. Opt. Soc. Am. A 30(12), 2595–2604 (2013).
[Crossref] [PubMed]

Wilson, M. C.

Wu, H.

H. Wu, X. Geng, X. Zhang, M. Qiu, K. Jiang, L. Tang, and J. Dong, “A self-adaptive distance regularized level set evolution method for optical disk segmentation,” Biomed. Mater. Eng. 24(6), 3199–3206 (2014).
[PubMed]

Zhang, X.

H. Wu, X. Geng, X. Zhang, M. Qiu, K. Jiang, L. Tang, and J. Dong, “A self-adaptive distance regularized level set evolution method for optical disk segmentation,” Biomed. Mater. Eng. 24(6), 3199–3206 (2014).
[PubMed]

Zhang, Y.

A. Roorda, Y. Zhang, and J. L. Duncan, “High-resolution in vivo imaging of the RPE mosaic in eyes with retinal disease,” Invest. Ophthalmol. Vis. Sci. 48(5), 2297–2303 (2007).
[Crossref] [PubMed]

Biomed. Mater. Eng. (1)

H. Wu, X. Geng, X. Zhang, M. Qiu, K. Jiang, L. Tang, and J. Dong, “A self-adaptive distance regularized level set evolution method for optical disk segmentation,” Biomed. Mater. Eng. 24(6), 3199–3206 (2014).
[PubMed]

Biomed. Opt. Express (2)

BMC Bioinformatics (1)

A. A. Hill, P. LaPan, Y. Li, and S. Haney, “Impact of image segmentation on high-content screening data quality for SK-BR-3 cells,” BMC Bioinformatics 8(1), 340 (2007).
[Crossref] [PubMed]

BMC Ophthalmol. (1)

K. Bredies, M. Wagner, C. Schubert, and P. Ahnelt, “Computer-assisted counting of retinal cells by automatic segmentation after TV denoising,” BMC Ophthalmol. 13(1), 59 (2013).
[Crossref] [PubMed]

Cytometry A (1)

A. A. Dima, J. T. Elliott, J. J. Filliben, M. Halter, A. Peskin, J. Bernal, M. Kociolek, M. C. Brady, H. C. Tang, and A. L. Plant, “Comparison of segmentation algorithms for fluorescence microscopy images of cells,” Cytometry A 79(7), 545–559 (2011).
[Crossref] [PubMed]

Electron. Lett. (1)

T. B. Tang, C. K. Lu, A. Laude, B. Dhillon, and A. F. Murray, “Noise reduction for ellipse fitting on medical images,” Electron. Lett. 49(3), 178–179 (2013).
[Crossref]

IEEE Signal Process. Mag. (1)

E. Meijering, “Cell Segmentation: 50 Years Down the Road,” IEEE Signal Process. Mag. 29(5), 140–145 (2012).
[Crossref]

Invest. Ophthalmol. Vis. Sci. (1)

A. Roorda, Y. Zhang, and J. L. Duncan, “High-resolution in vivo imaging of the RPE mosaic in eyes with retinal disease,” Invest. Ophthalmol. Vis. Sci. 48(5), 2297–2303 (2007).
[Crossref] [PubMed]

J. Cell Biol. (1)

Y. Imanishi, M. L. Batten, D. W. Piston, W. Baehr, and K. Palczewski, “Noninvasive two-photon imaging reveals retinyl ester storage structures in the eye,” J. Cell Biol. 164(3), 373–383 (2004).
[Crossref] [PubMed]

J. Opt. Soc. Am. A (1)

JAMA (1)

N. M. Bressler, “Age-related macular degeneration is the leading cause of blindness,” JAMA 291(15), 1900–1901 (2004).
[Crossref] [PubMed]

Nat. Med. (1)

G. Palczewska, Z. Dong, M. Golczak, J. J. Hunter, D. R. Williams, N. S. Alexander, and K. Palczewski, “Noninvasive two-photon microscopy imaging of mouse retina and retinal pigment epithelium through the pupil of the eye,” Nat. Med. 20(7), 785–789 (2014).
[Crossref] [PubMed]

Pattern Recognit. (1)

J. Kittler and J. Illingworth, “Minimum error thresholding,” Pattern Recognit. 19(1), 41–47 (1986).
[Crossref]

Physiol. Meas. (1)

R. Kolár, R. Laemmer, J. Jan, and ChY. Mardin, “The segmentation of zones with increased autofluorescence in the junctional zone of parapapillary atrophy,” Physiol. Meas. 30(5), 505–516 (2009).
[Crossref] [PubMed]

Proc. Natl. Acad. Sci. U.S.A. (2)

J.-D. Ding, L. V. Johnson, R. Herrmann, S. Farsiu, S. G. Smith, M. Groelle, B. E. Mace, P. Sullivan, J. A. Jamison, U. Kelly, O. Harrabi, S. S. Bollini, J. Dilley, D. Kobayashi, B. Kuang, W. Li, J. Pons, J. C. Lin, and C. Rickman, “Anti-amyloid therapy protects against retinal pigmented epithelium damage and vision loss in a model of age-related macular degeneration,” Proc. Natl. Acad. Sci. U.S.A. 108(28), E279–E287 (2011).
[Crossref] [PubMed]

A. Maeda, G. Palczewska, M. Golczak, H. Kohno, Z. Dong, T. Maeda, and K. Palczewski, “Two-photon microscopy reveals early rod photoreceptor cell damage in light-exposed mutant mice,” Proc. Natl. Acad. Sci. U.S.A. 111(14), E1428–E1437 (2014).
[Crossref] [PubMed]

Other (1)

K. Devisetti, T. P. Karnowski, L. Giancardo, Y. Li, and E. Chaum, “Geographic atrophy segmentation in infrared and autofluorescent retina images using supervised learning,” Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference 2011, 3958–3961 (2011).
[Crossref]

Supplementary Material (9)

NameDescription
» Visualization 1: MP4 (2739 KB)      Edge search
» Visualization 2: MP4 (647 KB)      Border tracing trials
» Visualization 3: MP4 (469 KB)      Pixel assignment to cell
» Visualization 4: MP4 (2234 KB)      4-week-old BALB/c mouse results
» Visualization 5: MP4 (2089 KB)      4-week-old BALB/c mouse results
» Visualization 6: MP4 (3380 KB)      2-month-old B6(Cg)-Tyrc-2J/J mouse results
» Visualization 7: MP4 (2835 KB)      2-month-old B6(Cg)-Tyrc-2J/J mouse results
» Visualization 8: MP4 (4154 KB)      10-month-old B6(Cg)-Tyrc-2J/J mouse results
» Visualization 9: MP4 (4494 KB)      10-month-old B6(Cg)-Tyrc-2J/J mouse results

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Figures (10)

Fig. 1
Fig. 1 Background correction improves nuclei segmentation when combined with non-background corrected nuclei segmentation. Pixels identified as being part of a nucleus are shown with zero intensity (black). A) Nuclei identified without background correction (same as Fig. 3(B) panel). B) Nuclei identified with background correction. C) The union of the pixels identified as nuclei from A) and B). D) Image from C) after noise filtering to remove false positive identification of nuclei pixels.
Fig. 2
Fig. 2 Initial steps of the RPE cell segmentation process. Cell segmentation uses as input A) a segmented nuclei image (here, the same as Fig. 1 A panel) and input B) the gradient image as calculated using the Sobel operator on the original image. C) The first step is to filter out noise segmented as nuclei. Accepted nuclei are shown with dark black outline. For an overview of the full process, see Visualization 1, Visualization 2, andVisualization 3 for demonstrations of drawing the searching segments, drawing the border, and assigning pixels to a cell, respectively.
Fig. 3
Fig. 3 Resulting identified nuclei after manually selected thresholding process. The pixels identified as being part of a nucleus are shown with zero intensity (black). A-B) 4-week-old BALB/c mice C-D) 2-month-old B6(Cg)-Tyrc-2J/J mice E-F) 10-month-old B6(Cg)-Tyrc-2J/J mice
Fig. 4
Fig. 4 Segmentation of RPE cells in six images of mice collected by TPM. Identified borders are shown as red lines around nuclei. A, B) Images collected from 4-week-old BALB/c mice corresponding to a and b in Table 1, respectively. Visualization 4 and Visualization 5 show which borders are considered successes, failures, and ignored from analysis for panels A and B, respectively. C, D) Images collected from 2-month-old B6(Cg)-Tyrc-2J/J mice corresponding to c and d in Table 1, respectively. Visualization 6 and Visualization 7 show which borders are considered successes, failures, and ignored from analysis for panels C and D, respectively. E, F) Images collected from 10-month-old B6(Cg)-Tyrc-2J/J mice corresponding to e and f in Table 1, respectively. Visualization 8 andVisualization 9 show which borders are considered successes, failures, and ignored from analysis for panels E and F, respectively.
Fig. 5
Fig. 5 Examples of three successful corrections of cell borders determined for nuclei in image a of a 4-week-old BALB/c mouse. The left images (A, C, E) show the border around a nucleus as initially determined. The right images (B, D, F) show the border around the corresponding nucleus (A, C, E, respectively) after revising the border as described in text. Borders are shown as red lines; pixels identified as nucleus are shown as black.
Fig. 6
Fig. 6 Kittler minimal error thresholding applied to a TPM RPE image. A) Starting image of 4-week-old BALB/c mouse. B-D) Thresholded images with nuclei identified as white pixels. Number of intensity bins is 10, 12, and 14 in B, C, and D, respectively.
Fig. 7
Fig. 7 Continued from Fig. 6, the process of segmenting the nuclei. A) After selecting the best thresholded image, the selected nuclei pixels are set to low intensity values on the original image. B) The image pixels are then averaged with the 9x9 box of pixels around each pixel. C-E) The blurred image (panel B) is then subjected to a second round of Kittler minimum error thresholding: the number of intensity bins here is 3, 4, and 6 for C, D, and E respectively. F) The pixels which are identified as belonging to a nucleus after the second round of thresholding are set to zero intensity.
Fig. 8
Fig. 8 Nuclei segmentation using background intensity correction and scored minimum error thresholding. A) The starting image (same as Fig. 6 A) of a 4-week-old BALB/c mouse RPE. B) The background illumination pattern. C) The original image (panel A) after subtracting the background illumination pattern. D) The best image which was selected by score after the image from C) was subjected to Kittler minimum error thresholding with multiple numbers of bins, as described in the text.
Fig. 9
Fig. 9 Continued from Fig. 8 the second round of thresholding on the background corrected image with noise filtering. A) Starting image after first round of thresholding. Nuclei are identified by black pixels. B) Image from panel A) after the pixels are averaged using the 9x9 set of pixels surrounding each pixel. C) Best image before filtering. D) Best image after filtering noise as described in the text. E) The original background corrected image with determined nuclei pixels set to intensity zero (black).
Fig. 10
Fig. 10 Initial stages of drawing a border. A) An eligible search region is defined with pixels that could be used to form the border, shown in white. B) Pixels are grouped into wedges of 21 degrees, starting at the upper left most pixel of the nucleus. Each wedge contains the pixels eligible to be vertices for edges. C) All pixels within the first wedge are scored and the pixel with the best score is selected. D) The border is continued by sampling nuclei from the next neighboring wedge, scoring all possible edges, selecting the best scoring edge, and repeating this process around the nucleus. See Visualization 1,Visualization 2, andVisualization 3 for demonstrations of drawing the searching segments, drawing the border, and assigning pixels to a cell, respectively.

Tables (2)

Tables Icon

Table 1 Success rate of identifying RPE borders over six imagesa.

Tables Icon

Table 2 Success rate of identifying RPE cell borders after revision of the borders.

Equations (2)

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row=row_start+( dist_fraction*( row_endrow_start ) ).
col=col_start+( dist_fraction*( col_endcol_start ) ).

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