Data for: Binary Tree-like Network with Two-path Fusion Attention Feature for Cervical Cell Nucleus Segmentation

Name: Data for: Binary Tree-like Network with Two-path Fusion Attention Feature for Cervical Cell Nucleus Segmentation
Creator: Jianwei Zhang
Published: 2019-04-18T04:19:38.574Z
Keywords: Medical Science, Computer Engineering

Zhang, Jianwei

doi:10.17632/jks43dkjj7.1

Data for: Binary Tree-like Network with Two-path Fusion Attention Feature for Cervical Cell Nucleus Segmentation

Published: 18 April 2019| Version 1 | DOI: 10.17632/jks43dkjj7.1

Contributor:

Jianwei Zhang

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The images are based on Liquid-Based Cytology test from the pathology departments of a Chinese hospital and a biomedical device company. Under the guidance of a professional pathologist, we choose qualified images in numerous LCT cervical images. The dataset contains 104 images with size and each image has a ground truth that has been manually segmented by a professional pathologist.

Data for: Binary Tree-like Network with Two-path Fusion Attention Feature for Cervical Cell Nucleus Segmentation

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