Case for automated detection of diabetic retinopathy

Nathan Silberman, Kristy Ahlrich, Robert Fergus, Lakshminarayanan Subramanian

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

Abstract

Diabetic retinopathy, an eye disorder caused by diabetes, is the primary cause of blindness in America and over 99% of cases in India. India and China currently account for over 90 million diabetic patients and are on the verge of an explosion of diabetic populations. This may result in an unprecedented number of persons becoming blind unless diabetic retinopathy can be detected early. Aravind Eye Hospitals is the largest eye care facility in the world, handling over 2 million patients per year. The hospital is on a massive drive throughout southern India to detect diabetic retinopathy at an early stage. To that end, a group of 10 - 15 physicians are responsible for manually diagnosing over 2 million retinal images per year to detect diabetic retinopathy. While the task is extremely laborious, a large fraction of cases turn out to be normal indicating that much of this time is spent diagnosing completely normal cases. This paper describes our early experiences working with Aravind Eye Hospitals to develop an automated system to detect diabetic retinopathy from retinal images. The automated diabetic retinopathy problem is a hard computer vision problem whose goal is to detect features of retinopathy, such as hemorrhages and exudates, in retinal color fundus images. We describe our initial efforts towards building such a system using a range of computer vision techniques and discuss the potential impact on early detection of diabetic retinopathy.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence for Development - Papers from the AAAI Spring Symposium, Technical Report
Pages85-90
Number of pages6
VolumeSS-10-01
StatePublished - 2010
Event2010 AAAI Spring Symposium - Stanford, CA, United States
Duration: Mar 22 2010Mar 24 2010

Other

Other2010 AAAI Spring Symposium
CountryUnited States
CityStanford, CA
Period3/22/103/24/10

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Computer vision
Medical problems
Explosions
Color

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Silberman, N., Ahlrich, K., Fergus, R., & Subramanian, L. (2010). Case for automated detection of diabetic retinopathy. In Artificial Intelligence for Development - Papers from the AAAI Spring Symposium, Technical Report (Vol. SS-10-01, pp. 85-90)

Case for automated detection of diabetic retinopathy. / Silberman, Nathan; Ahlrich, Kristy; Fergus, Robert; Subramanian, Lakshminarayanan.

Artificial Intelligence for Development - Papers from the AAAI Spring Symposium, Technical Report. Vol. SS-10-01 2010. p. 85-90.

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

Silberman, N, Ahlrich, K, Fergus, R & Subramanian, L 2010, Case for automated detection of diabetic retinopathy. in Artificial Intelligence for Development - Papers from the AAAI Spring Symposium, Technical Report. vol. SS-10-01, pp. 85-90, 2010 AAAI Spring Symposium, Stanford, CA, United States, 3/22/10.
Silberman N, Ahlrich K, Fergus R, Subramanian L. Case for automated detection of diabetic retinopathy. In Artificial Intelligence for Development - Papers from the AAAI Spring Symposium, Technical Report. Vol. SS-10-01. 2010. p. 85-90
Silberman, Nathan ; Ahlrich, Kristy ; Fergus, Robert ; Subramanian, Lakshminarayanan. / Case for automated detection of diabetic retinopathy. Artificial Intelligence for Development - Papers from the AAAI Spring Symposium, Technical Report. Vol. SS-10-01 2010. pp. 85-90
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