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 IDBIO-2.3
Paper Title WEAKLY-SUPERVISED AUTOMATIC BIOMARKERS DETECTION AND CLASSIFICATION OF RETINAL OPTICAL COHERENCE TOMOGRAPHY IMAGES
Authors Xiaoming Liu, Zhipeng Liu, Wuhan University of Science and Technology, China; Ying Zhang, Man Wang, Wuhan Aier Eye Hospital, China; Bo Li, Wuhan University of Science and Technology, China; Jinshan Tang, George Mason University, United States
SessionBIO-2: Biomedical Signal Processing 2
LocationArea D
Session Time:Tuesday, 21 September, 08:00 - 09:30
Presentation Time:Tuesday, 21 September, 08:00 - 09:30
Presentation Poster
Topic Biomedical Signal Processing: Medical image analysis
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Abstract Optical coherence tomography (OCT) is a primary imaging technique for ophthalmic diagnosis, which has been widely used in retinal disease diagnosis. The retinal biological markers, or biomarkers, play an important role in the management of chronic eye conditions. Hence, it is critical to detect and classify biomarkers from OCT B-scan for patients. In this paper, we proposed a novel weakly-supervised approach utilized healthy data and image-level labels through integrating adversarial generative network and guided attention into one framework. The framework includes an anomaly detection network and a classification network. The anomaly detection network reconstructs the input images with biomarkers to the normal and compared to locate biomarkers area. Inspired by guided attention in network, we utilized the discriminator trained in the anomaly detection network as a classifier twice to reduce model parameters and obtain a complete attention map with class information to get biomarkers classes. Experiment results on a large dataset demonstrate the effectiveness of the proposed detection and classification framework.