FAST Text Pipelines

Ultrasound segmentation of jugular and carotid

This pipeline uses a neural network to segment the jugular vein and carotid artery from ultrasound images.

ID: jugular-carotid-ultrasound-segmentation
Downloads: 6
Authors: Erik Smistad
Copyrights: SINTEF
Licenses: CC BY 4.0 CC BY-SA 4.0

Breast Tumour Segmentation

A pipeline for segmenting breast cancer tumour region from a whole-slide image using the H2G-Net model: https://github.com/andreped/H2G-Net

ID: breast-tumour-segmentation
Downloads: 16
Authors: André Pedersen
Copyrights: NTNU
Licenses: CC BY 4.0

Breast Tumour Segmentation

A FastPathology pipeline for segmenting breast cancer tumour region from a whole-slide image using the H2G-Net model: https://github.com/andreped/H2G-Net

ID: breast-tumour-segmentation-fp
Downloads: 5
Authors: André Pedersen
Copyrights: NTNU
Licenses: CC BY 4.0

BACH Classification

Patch-wise image classification model trained on data from the 2018 breast cancer histology (BACH) challenge: https://iciar2018-challenge.grand-challenge.org/

ID: bach-classification-fp
Downloads: 3
Authors: André Pedersen
Copyrights: NTNU
Licenses: CC BY 4.0

Nuclei segmentation

A FastPathology pipeline for patch-wise segmentation of cell nuclei at 20X magnification using a lightweight U-Net. Trained on PanNuke dataset.

ID: nuclei-segmentation-fp
Downloads: 3
Authors: André Pedersen
Copyrights: NTNU
Licenses: CC BY 4.0

Nuclei Classification (PanNuke, 20X, HoVerNet)

This pipeline segments cell nuclei into one of 5 different classes: Neoplastic, Inflammatory, Connective, Dead, Non-Neoplastic Epithelial. The model is trained on the PanNuke dataset using the HoVerNet architecture. The model is part of the publication "A Pragmatic Machine Learning Approach to Quantify Tumor-Infiltrating Lymphocytes in Whole Slide Images" Cancers 2022 https://doi.org/10.3390/cancers14122974

ID: nuclei-classification-hovernet-pannuke-20x-fp
Downloads: 3
Authors: Nikita Shvetsov, Morten Grønnesby, Edvard Pedersen, Kajsa Møllersen, Lill-Tove Rasmussen Busund, Ruth Schwienbacher, Lars Ailo Bongo, Thomas Karsten Kilvaer
Copyrights: UiT - The Arctic University of Norway
Licenses: CC SA-BY-NC 4.0

Epithelium segmentation in colonic mucosa (CD3-stained)

FastPathology pipeline for segmentation of epithelial cells in CD3-stained biopsies of colonic mucosa of active and inactivate inflammatory bowel disease. For more info see the article "Code-Free Development and Deployment of Deep Segmentation Models for Digital Pathology" Frontiers in Medicine 2022 https://www.frontiersin.org/articles/10.3389/fmed.2021.816281/full and also the webpage https://github.com/andreped/NoCodeSeg.

ID: colon-epithelium-segmentation-cd3-fp
Downloads: 1
Authors: André Pedersen, Henrik Sahlin Pettersen, Ilya Belevich, Elin Synnøve Røyset, Erik Smistad, Melanie Rae Simpson, Eija Jokitalo, Ingerid Reinertsen, Ingunn Bakke, André Pedersen
Copyrights: NTNU, St. Olavs Hospital, SINTEF, University of Helsinki
Licenses: GPL 2.0

Epithelium segmentation in colonic mucosa (HE-stained)

Segmentation of epithelial cells in HE-stained biopsies of colonic mucosa of active and inactivate inflammatory bowel disease. For more info see the article "Code-Free Development and Deployment of Deep Segmentation Models for Digital Pathology" Frontiers in Medicine 2022 https://www.frontiersin.org/articles/10.3389/fmed.2021.816281/full and also the webpage https://github.com/andreped/NoCodeSeg.

ID: colon-epithelium-segmentation-he-fp
Downloads: 1
Authors: André Pedersen, Henrik Sahlin Pettersen, Ilya Belevich, Elin Synnøve Røyset, Erik Smistad, Melanie Rae Simpson, Eija Jokitalo, Ingerid Reinertsen, Ingunn Bakke, André Pedersen
Copyrights: NTNU, St. Olavs Hospital, SINTEF, University of Helsinki
Licenses: GPL 2.0