Y-Net Automatic brain tumor segmentation software based on deep learning method

Introduction

Our software contains an end-to-end CNN segmentation network, which uses only two adjacent images instead of the target image as the input data of the deep neural network to predict the brain tumor area in the target image. This method avoids noise interference in the target image and makes full use of the spatial context features between adjacent slices to obtain accurate brain tumor segmentation results.

Publications

  1. A Zero-Shot Method for 3D Medical Image Segmentation
    Shiqiang Ma, Xuejian Li, Jijun Tang, Fei Guo, 2021/6/9 - 2021 IEEE International Conference on Multimedia and Expo (ICME)

Credits

  1. Fei Guo fguo@tju.edu.cn
    Investigator

    School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, China

  2. Shiqiang Ma shiqiang@tju.edu.cn
    Developer

    School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, China

  3. Xuejian Li lixuejian@tju.edu.cn
    Developer

    School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, China

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Summary
AccessionBT007128
Tool TypeApplication
CategoryImage segmentation
PlatformsLinux/Unix
TechnologiesPython3
User InterfaceTerminal Command Line
Latest Release1.0 (May 29, 2021)
Download Count101
Country/RegionChina
Submitted ByFei Guo
Fundings

2018YFC0910400