Generative caption for diabetic retinopathy images

Luhui Wu, Cheng Wan, Yiquan Wu, Jiang Liu

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

For a long time, the detection of diabetic retinopathy has always been a great challenge. People want to find a fast and effective computer-aided treatment to diagnose the disease. In recent years, the rapid development of the deep learning makes it gradually become an effective technique for the analysis of medical images. In this paper, we propose a method to deal with diabetic retinopathy images with generative caption technique of images to generate a simple sequence to explain the abnormal contents in fundus images. The generative technique of images is a generative model based on a deep recurrent architecture that combines convolution neural network (CNN) which is currently state-of-the-art for object recognition and detection with long-short-term-memory (LSTM) which is applied with great success to machine translation and sequence generation, and that can be used to generate natural sentences describing an image. The target of the model in training is to maximize the likelihood of the target description sentence given from the training images. The model built on dataset DIARETDB0, DIARETDB1 and Messidor can achieve good performance and generate fluent sequences. In addition, the experimental results show that the accuracy of diagnosis for individual abnormal discoveries is up to 88.53% and the diagnosis accuracy is more than 90%.

Original languageEnglish
Title of host publication2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages515-519
Number of pages5
ISBN (Electronic)9781538630167
DOIs
Publication statusPublished - 27 Feb 2018
Externally publishedYes
Event2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017 - Shenzhen, China
Duration: 15 Dec 201717 Dec 2017

Publication series

Name2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017
Volume2018-January

Conference

Conference2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017
Country/TerritoryChina
CityShenzhen
Period15/12/1717/12/17

Keywords

  • Deep Learning
  • Diabetic Retinopathy
  • Image Caption
  • Retinopathy Lesions

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications

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