Development of a pathological image analysis and cell classification pipeline with convolutional neural network
Principal Investigator
Name
Honglei Zhang
Degrees
Ph.D
Institution
Yunnan University of Traditional Chinese Medicine
Position Title
Professor
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-1036
Initial CDAS Request Approval
Mar 30, 2023
Title
Development of a pathological image analysis and cell classification pipeline with convolutional neural network
Summary
In this study, we plan to develop an automated cell type classification pipeline, which includes nuclei segmentation, tumor cell, stromal cell, and lymphocyte classification, and extraction of tumor microenvironment-related features for lung cancer pathology images. The analysis pipeline developed in this study could greatly facilitate and empower comprehensive analysis of the spatial organization of cells, as well as their roles in tumor progression and metastasis. To achieve this goal we need pathology images and clinical data of lung cancer in the NLST as validation dataset.
Aims
1.Develop an automated cell type classification pipeline, which includes nuclei segmentation, convolutional neural network-based tumor cell, stromal cell, and lymphocyte classification, and extraction of tumor microenvironment-related features for lung cancer pathology images.
Collaborators
There are no other collaborators.