histocartography.preprocessing.nuclei_concept_extraction module¶

Extract features from images for a given structure

Summary¶

Classes:

NucleiConceptExtractor

Class for Nuclei concept extraction.

class NucleiConceptExtractor(concept_names=None, **kwargs)[source]¶

Bases: histocartography.pipeline.PipelineStep

Class for Nuclei concept extraction. Extract nuclei-level measurable concepts.

__init__(concept_names=None, **kwargs) → None[source]¶

Nuclei Concept Extractor constructor.

Parameters

concept_names (str) –

List of all the concepts to extract. Default to ‘’.: If set to None, extract all the concepts. Otherwise, extract all the listed concepts

separated with commas, eg. ‘area,perimeter,eccentricity’.

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}
}