A computer‐aided diagnostic system for detecting diabetic retinopathy in optical coherence tomography images

Purpose Detection (diagnosis) of diabetic retinopathy (DR) in optical coherence tomography (OCT) images for patients with type 2 diabetes, but almost clinically normal retina appearances. Methods The proposed computer‐aided diagnostic (CAD) system detects the DR in three steps: (a) localizing and se...

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Veröffentlicht in:	Medical physics (Lancaster) Jg. 44; H. 3; S. 914 - 923
Hauptverfasser:	ElTanboly, Ahmed, Ismail, Marwa, Shalaby, Ahmed, Switala, Andy, El‐Baz, Ayman, Schaal, Shlomit, Gimel’farb, Georgy, El‐Azab, Magdi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 01.03.2017
Schlagworte:	Adult Aged diabetic retinopathy (DR) Diabetic Retinopathy - diagnostic imaging Female Humans Image Interpretation, Computer-Assisted - methods joint image‐region‐map model Machine Learning Male Markov–Gibbs random field (MGRF) Middle Aged non‐negativity‐constrained autoencoder (NCAE) optical coherence tomography (OCT) Pattern Recognition, Automated Retina - diagnostic imaging Sensitivity and Specificity Tomography, Optical Coherence - methods joint image-region-map model Markov-Gibbs random field (MGRF) non-negativity-constrained autoencoder (NCAE) optical coherence tomography (OCT) diabetic retinopathy (DR)
ISSN:	0094-2405, 2473-4209, 2473-4209
Online-Zugang:	Volltext
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