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Lung Preneoplasia Progression via Pathomics

License: BSD 3-Clause "New" or "Revised" License

Python 97.77% Dockerfile 2.23%

biomedical-image-analysis computational-pathology lung-cancer pathology-image pathomics lung-preneoplasia neoplasm-evolution

lungevolutionpathomics's Introduction

LungEvolutionPathomics

Pipeline of investigating lung preneoplasia evolution via pathomics

Data to reproduce the results was deposited in Mendeley Data
NucleiSegHE was used to generate ROI-level nuclei segmentation
Pipeline illustrating the general study design of lung preneoplasia evolution via pathomics

Environment Configurations

a. Prepare docker image

Build from Dockerfile

$ docker build -t lung_evolution_pathomics:chen .

Or pull from Docker Hub

$ docker pull pingjunchen/lung_evolution_pathomics:chen
$ docker tag pingjunchen/lung_evolution_pathomics:chen lung_evolution_pathomics:chen

b. Setup docker container

Start docker container (specify CODE_ROOT & DATA_ROOT)

$ docker run -it --rm --user $(id -u):$(id -g) \
  -v ${CODE_ROOT}:/App/LungEvolutionPathomics \
  -v ${DATA_ROOT}:/Data \
  --shm-size=168G --gpus '"device=0"' --cpuset-cpus=10-39 \
  --name lung_evolution_pathomics_chen lung_evolution_pathomics:chen

Pathomic Features Evaluating Lung Preneoplasia Evolution

1. Evolution trends along with pathological stage progression

2. Correlation with a series of molecular markers

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