Exudate-based diabetic macular edema detection in fundus images using publicly available datasets

Journal Article · Fri Jul 01 04:00:00 EDT 2011 · Medical Image Analysis

DOI:https://doi.org/10.1016/j.media.2011.07.004· OSTI ID:1036199

Giancardo, Luca ^[1]; Meriaudeau, Fabrice ^[1]; Karnowski, Thomas ^[1]; Li, Yi-Liang ^[2]; Garg, Seema ^[3]; Tobin Jr, Kenneth ^[1]; Chaum, Ed ^[2]

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1. ORNL
2. University of Tennessee, Knoxville (UTK)
3. University of North Carolina

Diabetic macular edema (DME) is a common vision threatening complication of diabetic retinopathy. In a large scale screening environment DME can be assessed by detecting exudates (a type of bright lesions) in fundus images. In this work, we introduce a new methodology for diagnosis of DME using a novel set of features based on colour, wavelet decomposition and automatic lesion segmentation. These features are employed to train a classifier able to automatically diagnose DME through the presence of exudation. We present a new publicly available dataset with ground-truth data containing 169 patients from various ethnic groups and levels of DME. This and other two publicly available datasets are employed to evaluate our algorithm. We are able to achieve diagnosis performance comparable to retina experts on the MESSIDOR (an independently labelled dataset with 1200 images) with cross-dataset testing (e.g., the classifier was trained on an independent dataset and tested on MESSIDOR). Our algorithm obtained an AUC between 0.88 and 0.94 depending on the dataset/features used. Additionally, it does not need ground truth at lesion level to reject false positives and is computationally efficient, as it generates a diagnosis on an average of 4.4 s (9.3 s, considering the optic nerve localization) per image on an 2.6 GHz platform with an unoptimized Matlab implementation.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1036199
• Journal Information: Medical Image Analysis, Journal Name: Medical Image Analysis Journal Issue: 7 Vol. 16
• Country of Publication: United States
• Language: English

Related Subjects

59 BASIC BIOLOGICAL SCIENCES
60 APPLIED LIFE SCIENCES
99 GENERAL AND MISCELLANEOUS
ALGORITHMS
DETECTION
DIABETES MELLITUS
DIAGNOSIS
EDEMA
EYES
GROUND TRUTH MEASUREMENTS
IMPLEMENTATION
MINORITY GROUPS
NERVES
PATIENTS
PERFORMANCE
PROBABILITY
RETINA
TESTING
VISION