Refined Deep Neural Network and U-Net for Polyps Segmentation
- University of Science, VNU-HCM（胡志明市国家大学科学大学）
- John von Neumann Institute, VNU-HCM（胡志明市国家大学约翰·冯·诺依曼研究所）
- Vietnam National University, Ho Chi Minh city（越南国家大学胡志明市分校）
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英文摘要：
The Medico: Multimedia Task 2020 focuses on developing an efficient and accurate computer-aided diagnosis system for automatic segmentation [3]. We participate in task 1, Polyps segmentation task, which is to develop algorithms for segmenting polyps on a comprehensive dataset. In this task, we propose methods combining Residual module, Inception module, Adaptive Convolutional neural network with U-Net model, and PraNet for semantic segmentation of various types of polyps in endoscopic images. We select 5 runs with different architecture and parameters in our methods. Our methods show potential results in accuracy and efficiency through multiple experiments, and our team is in the Top 3 best results with a Jaccard index of 0.765.
