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CSM-Net: A Multi-Task Colorectal Cancer Analysis Framework

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Abstract

Colorectal cancer is the second leading cause of cancer mortality before 2020, in this paper, we propose a simple yet efficient anchor-free instance segmentation framework, Colorectal Spatial Mask Network, aiming at jointly detecting and segmenting the tumor region in colorectal cancer MRI image series. we add a novel spatial attention-guided mask branch to anchor-free one stage object detector into the framework with the same way in Mask R-CNN. In addition, we also employ an improved network VoVNetV2 as the new backbone network. After comparison with the state-of-the-arts methods, the results of experiments reveal that our framework can get well balance between speed and accuracy.

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Acknowledgements

This research is supported by National Natural Science Foundation of China (Grant No. 61702026), The Pyramid Talent Training Project of BUCEA (Grant No. JDYC20200318), Harbin Applied Technology Research and Development Program under Grant 2017RAQXJ096.

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China

    Dong Sui, Yimeng Zhang & Guangzhe Zhao

  2. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Zhaoxin Li

  3. Zhou-Kou-Dian Middle School, Beijing, China

    Yantao Wang

  4. College of Arts and Sciences, Northeast Agricultural University, Harbin, China

    Qiufeng Wu

  5. Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, MD, USA

    Lei Zhang

  6. Heilongjiang Civil Affairs Information Service Center, Harbin, China

    Rui Zhang

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  1. Dong Sui
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Correspondence to Guangzhe Zhao.

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Sui, D., Zhang, Y., Li, Z. et al. CSM-Net: A Multi-Task Colorectal Cancer Analysis Framework. Sens Imaging 21, 42 (2020). https://doi.org/10.1007/s11220-020-00307-1

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