2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDSS-MIA.1
Paper Title Deep Context-Encoding Network for Retinal Image Captioning
Authors Jia-Hong Huang, University of Amsterdam, Netherlands; Ting-Wei Wu, C.-H. Huck Yang, Georgia Institute of Technology, United States; Marcel Worring, University of Amsterdam, Netherlands
SessionSS-MIA: Special Session: Deep Learning and Precision Quantitative Imaging for Medical Image Analysis
LocationArea A
Session Time:Wednesday, 22 September, 14:30 - 16:00
Presentation Time:Wednesday, 22 September, 14:30 - 16:00
Presentation Poster
Topic Special Sessions: Deep Learning and Precision Quantitative Imaging for Medical Image Analysis
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Automatically generating medical reports for retinal images is one of the promising ways to help ophthalmologists reduce their workload and improve work efficiency. In this work, we propose a new context-driven encoding network to automatically generate medical reports for retinal images. The proposed model is mainly composed of a multi-modal input encoder and a fused-feature decoder. Our experimental results show that our proposed method is capable of effectively leveraging the interactive information between the input image and context, i.e., keywords in our case. The proposed method creates more accurate and meaningful reports for retinal images than baseline models and achieves state-of-the-art performance. This performance is shown in several commonly used metrics for the medical report generation task: BLEU-avg (+16%), CIDEr (+10.2%), and ROUGE (+8.6%).