4.5 Article

Diabetic macular edema grading based on improved Faster R-CNN and MD-ResNet

Journal

SIGNAL IMAGE AND VIDEO PROCESSING
Volume 15, Issue 4, Pages 743-751

Publisher

SPRINGER LONDON LTD
DOI: 10.1007/s11760-020-01792-3

Keywords

Diabetic macular edema; Faster R-CNN; Macular center; Hard Exudates; Multi-level feature with deconvolution residual network

Funding

  1. National Natural Science Foundation of China [61601325]
  2. Tianjin Science and Technology Major Projects and Engineering [17ZXSCSY00060, 17ZXHLSY00040]
  3. Program for Innovative Research Team in University of Tianjin [TD13-5034]

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Early detection and accurate grading of DME is crucial for reducing the risk of vision loss in diabetic patients. The proposed DME grading method showed high accuracy in testing, improving efficiency and saving medical resources compared to other commonly used methods.
Diabetic macular edema (DME) is the main cause of visual impairment in diabetic patients. Early detection of DME will significantly reduce the risk of vision loss for the patients. According to the clinical DME grading standard, the positional relationship between Hard Exudates (HEs) and macular center is an important basis for DME grading. Accurate DME grading is thus predicated on properly locating the macular center and segmenting HEs. HEI-MED and E-ophtha EX data sets were tested by the proposed DME grading method, reaching an average accuracy of 94.4% and 87%, respectively. The proposed method was also tested by comparison against other commonly used methods as per its potential to assist doctors in initially screening DME; it was found to not only improve the efficiency of DME detection, but also to save Optical Coherence Tomography medical resources over the other methods tested.

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