Welcome to histocartography’s documentation!¶
histocartography is a python-based library designed to facilitate the development of graph-based computational pathology pipelines. The library includes plug-and-play modules to perform:
standard histology image pre-processing (e.g., stain normalization, nuclei detection, tissue detection)
entity-graph representation building (e.g. cell graph, tissue graph, hierarchical graph)
modeling Graph Neural Networks (e.g. GIN, PNA)
feature attribution based graph interpretability techniques (e.g. GraphGradCAM, GraphGradCAM++, GNNExplainer)
visualization tools
All the functionalities are grouped under a user-friendly API.
- histocartography package
- histocartography.pipeline module
- histocartography.interpretability package
- histocartography.metrics package
- histocartography.ml package
- histocartography.preprocessing package
- histocartography.preprocessing.assignment_matrix module
- histocartography.preprocessing.feature_extraction module
- histocartography.preprocessing.graph_builders module
- histocartography.preprocessing.io module
- histocartography.preprocessing.nuclei_concept_extraction module
- histocartography.preprocessing.nuclei_extraction module
- histocartography.preprocessing.stain_normalizers module
- histocartography.preprocessing.stats module
- histocartography.preprocessing.superpixel module
- histocartography.preprocessing.tissue_mask module
- histocartography.preprocessing.utils module
- Summary
- Reference
- histocartography.utils package
- histocartography.visualization package
- Summary
- Reference
Indices and tables¶
Reference¶
If you use histocartography in your projects, please cite the following:
@inproceedings{pati2021,
title = {Hierarchical Graph Representations for Digital Pathology},
author = {Pushpak Pati, Guillaume Jaume, Antonio Foncubierta, Florinda Feroce, Anna Maria Anniciello, Giosuè Scognamiglio, Nadia Brancati, Maryse Fiche, Estelle Dubruc, Daniel Riccio, Maurizio Di Bonito, Giuseppe De Pietro, Gerardo Botti, Jean-Philippe Thiran, Maria Frucci, Orcun Goksel, Maria Gabrani},
booktitle = {https://arxiv.org/pdf/2102.11057},
year = {2021}
}