Analyzing OCT images of age-related macular degeneration patients to identify spatial health correlations

Susannah Go, Parvathi Chundi, Mahadevan Subramaniam, Eyal Margalit

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

An approach to automatically group age-related macular degeneration (AMD) patients having similar retinal health profiles by clustering Optical Coherence Tomography (OCT) images is described. Spatial health patterns within and across profiles are discovered by identifying segments of images that have similar levels of health in a given retina region. Segmentations of various sizes are considered and the segmentation where the segment similarity most closely matches the discovered health profiles is used to identify health patterns. Our experiments with OCT images of 10 AMD patients show that - i) health profiles generated by clustering closely correspond to those identified by a physician expert, ii) a rich set of spatial patterns can be discovered within and across profiles using regular image segmentation, and iii) new images can be successfully classified into existing profiles so that physicians can provide effective profile-based treatments.

Original languageEnglish (US)
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages8127-8130
Number of pages4
ISBN (Electronic)9781424492718
DOIs
StatePublished - Nov 4 2015
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: Aug 25 2015Aug 29 2015

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
CountryItaly
CityMilan
Period8/25/158/29/15

Fingerprint

Optical tomography
Optical Coherence Tomography
Macular Degeneration
Health
Cluster Analysis
Physicians
Health Status
Retina
Image segmentation
Experiments

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Go, S., Chundi, P., Subramaniam, M., & Margalit, E. (2015). Analyzing OCT images of age-related macular degeneration patients to identify spatial health correlations. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 (pp. 8127-8130). [7320280] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2015-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2015.7320280

Analyzing OCT images of age-related macular degeneration patients to identify spatial health correlations. / Go, Susannah; Chundi, Parvathi; Subramaniam, Mahadevan; Margalit, Eyal.

2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 8127-8130 7320280 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2015-November).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Go, S, Chundi, P, Subramaniam, M & Margalit, E 2015, Analyzing OCT images of age-related macular degeneration patients to identify spatial health correlations. in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015., 7320280, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2015-November, Institute of Electrical and Electronics Engineers Inc., pp. 8127-8130, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015, Milan, Italy, 8/25/15. https://doi.org/10.1109/EMBC.2015.7320280
Go S, Chundi P, Subramaniam M, Margalit E. Analyzing OCT images of age-related macular degeneration patients to identify spatial health correlations. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 8127-8130. 7320280. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/EMBC.2015.7320280
Go, Susannah ; Chundi, Parvathi ; Subramaniam, Mahadevan ; Margalit, Eyal. / Analyzing OCT images of age-related macular degeneration patients to identify spatial health correlations. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 8127-8130 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).
@inproceedings{66e06a67604e47b592c680b8024ba25d,
title = "Analyzing OCT images of age-related macular degeneration patients to identify spatial health correlations",
abstract = "An approach to automatically group age-related macular degeneration (AMD) patients having similar retinal health profiles by clustering Optical Coherence Tomography (OCT) images is described. Spatial health patterns within and across profiles are discovered by identifying segments of images that have similar levels of health in a given retina region. Segmentations of various sizes are considered and the segmentation where the segment similarity most closely matches the discovered health profiles is used to identify health patterns. Our experiments with OCT images of 10 AMD patients show that - i) health profiles generated by clustering closely correspond to those identified by a physician expert, ii) a rich set of spatial patterns can be discovered within and across profiles using regular image segmentation, and iii) new images can be successfully classified into existing profiles so that physicians can provide effective profile-based treatments.",
author = "Susannah Go and Parvathi Chundi and Mahadevan Subramaniam and Eyal Margalit",
year = "2015",
month = "11",
day = "4",
doi = "10.1109/EMBC.2015.7320280",
language = "English (US)",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "8127--8130",
booktitle = "2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015",

}

TY - GEN

T1 - Analyzing OCT images of age-related macular degeneration patients to identify spatial health correlations

AU - Go, Susannah

AU - Chundi, Parvathi

AU - Subramaniam, Mahadevan

AU - Margalit, Eyal

PY - 2015/11/4

Y1 - 2015/11/4

N2 - An approach to automatically group age-related macular degeneration (AMD) patients having similar retinal health profiles by clustering Optical Coherence Tomography (OCT) images is described. Spatial health patterns within and across profiles are discovered by identifying segments of images that have similar levels of health in a given retina region. Segmentations of various sizes are considered and the segmentation where the segment similarity most closely matches the discovered health profiles is used to identify health patterns. Our experiments with OCT images of 10 AMD patients show that - i) health profiles generated by clustering closely correspond to those identified by a physician expert, ii) a rich set of spatial patterns can be discovered within and across profiles using regular image segmentation, and iii) new images can be successfully classified into existing profiles so that physicians can provide effective profile-based treatments.

AB - An approach to automatically group age-related macular degeneration (AMD) patients having similar retinal health profiles by clustering Optical Coherence Tomography (OCT) images is described. Spatial health patterns within and across profiles are discovered by identifying segments of images that have similar levels of health in a given retina region. Segmentations of various sizes are considered and the segmentation where the segment similarity most closely matches the discovered health profiles is used to identify health patterns. Our experiments with OCT images of 10 AMD patients show that - i) health profiles generated by clustering closely correspond to those identified by a physician expert, ii) a rich set of spatial patterns can be discovered within and across profiles using regular image segmentation, and iii) new images can be successfully classified into existing profiles so that physicians can provide effective profile-based treatments.

UR - http://www.scopus.com/inward/record.url?scp=84953256376&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84953256376&partnerID=8YFLogxK

U2 - 10.1109/EMBC.2015.7320280

DO - 10.1109/EMBC.2015.7320280

M3 - Conference contribution

C2 - 26738180

AN - SCOPUS:84953256376

T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

SP - 8127

EP - 8130

BT - 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015

PB - Institute of Electrical and Electronics Engineers Inc.

ER -