W-Net: A Two-Stage Convolutional Network for Nucleus Detection in Histopathology Image

no code implementations • 26 Oct 2021 • Anyu Mao, Jialun Wu, Xinrui Bao, Zeyu Gao, Tieliang Gong, Chen Li

In order to take advantage of segmentation methods based on point annotation, further alleviate the manual workload, and make cancer diagnosis more efficient and accurate, it is necessary to develop an automatic nucleus detection algorithm, which can automatically and efficiently locate the position of the nucleus in the pathological image and extract valuable information for pathologists.

Cell Detection Segmentation

A Precision Diagnostic Framework of Renal Cell Carcinoma on Whole-Slide Images using Deep Learning

no code implementations • 26 Oct 2021 • Jialun Wu, Haichuan Zhang, Zeyu Gao, Xinrui Bao, Tieliang Gong, Chunbao Wang, Chen Li

Tumor region detection, subtype and grade classification are the fundamental diagnostic indicators for renal cell carcinoma (RCC) in whole-slide images (WSIs).

Classification whole slide images

PIMIP: An Open Source Platform for Pathology Information Management and Integration

no code implementations • 9 Nov 2021 • Jialun Wu, Anyu Mao, Xinrui Bao, Haichuan Zhang, Zeyu Gao, Chunbao Wang, Tieliang Gong, Chen Li

However, there is still a lack of an open and universal digital pathology platform to assist doctors in the management and analysis of digital pathological sections, as well as the management and structured description of relevant patient information.

Management