ImmunoAIzer: A deep-learning-based computational framework to characterize cell distribution and gene mutation in tumor microenvironment. Chang Bian et al.

Published: 20-04-2021| Version 1 | DOI: 10.17632/6rkw48wspj.1
Contributor:
chang bian

Description

This dataset contains the original unprocessed H&E and mIHC image slides of the paper:"ImmunoAIzer: A deep-learning-based computational framework to characterize cell distribution and gene mutation in tumor microenvironment". The original data of the paper contains 8 H&E WSIs and their corresponding mIHC WSIs. The slides are stored in qptiff format, which can be viewed by phenochart software or any other WSI viewing softwares. Because the original file size is about 30GB after compressing and the available storage of mendeley data project is 10GB, we only uploaded the H&E WSI and its corresponding mIHC WSI of 1 tissue sample. The whole original dataset can be accessed by reasonable request.

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Steps to reproduce

Steps to reproduce are illustrated in the paper.