Information Fusion for Colorectal Polyps Medical Image Segmentation

Author(s): Zhuo Zhou, Yinghua Duan, Weilan Huang, Fengyun Pei, Bo Liu, Jun Huang

Training a deep neural network often requires a large amount of annotated data, which is scarce in the medical image analysis domain. In this work, we present a simple yet effective technique for enhancing medical image segmentation neural network through information fusion. The proposed approach utilizes information from different spatial scales and combines them in a learnable way. Experimental results on two benchmark datasets demonstrate that the proposed fusion module improves the segmentation performance of state-of-the-art neural networks.

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