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: 9
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: 27
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: 76
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: 63
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: 80
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: 54
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: 42
Authors: Henrik Sahlin Pettersen, Ilya Belevich, Elin Synnøve Røyset, Erik Smistad, Melanie Rae Simpson, Eija Jokitalo, Ingerid Reinertsen, Ingunn Bakke, André Pedersen, 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: 57
Authors: Henrik Sahlin Pettersen, Ilya Belevich, Elin Synnøve Røyset, Erik Smistad, Melanie Rae Simpson, Eija Jokitalo, Ingerid Reinertsen, Ingunn Bakke, André Pedersen, André Pedersen
Copyrights: NTNU, St. Olavs Hospital, SINTEF, University of Helsinki
Licenses:
GPL 2.0
Brain MRI Segmentation
A pipeline for segmenting the brain from an MRI image
ID: brain-mri-segmentation
Downloads: 9
Authors: David Bouget, S. Bakas, C. Sako, H. Akbari, M. Bilello, A. Sotiras, G. Shukla, J. D. Rudie, N. Flores Santamaria, A. Fathi Kazerooni, S. Pati, S. Rathore, E. Mamourian, S. M. Ha, W. Parker, J. Doshi, U. Baid, M. Bergman, Z. A. Binder, R. Verma, R. Lustig, A. S. Desai, S. J. Bagley, Z. Mourelatos, J. Morrissette, C. D. Watt, S. Brem, R. L. Wolf, E. R. Melhem, M. P. Nasrallah, S. Mohan, D. M. O’Rourke, C. Davatzikos
Copyrights: The Cancer Imaging Archive, SINTEF
Licenses:
CC BY 4.0
BSD 2-Clause
Brain Tumor Segmentation
Segment brain tumors from T1 MRI using AGU-Net. The method is described in the article "Preoperative Brain Tumor Imaging: Models and Software for Segmentation and Standardized Reporting" Frontiers in Neurology 2022: https://doi.org/10.3389/fneur.2022.932219
ID: brain-mri-hgg-tumor-segmentation
Downloads: 3
Authors: David Bouget, André Pedersen, Asgeir S. Jakola, Vasileios Kavouridis, Kyrre E. Emblem, Roelant S. Eijgelaar, Ivar Kommers, Hilko Ardon, Frederik Barkhof, Lorenzo Bello, Mitchel S. Berger, Marco Conti Nibali, Julia Furtner, Shawn Hervey-Jumper, Albert J. S. Idema, Barbara Kiesel, Alfred Kloet, Emmanuel Mandonnet, Domenique M. J. Müller, Pierre A. Robe, Marco Rossi, Tommaso Sciortino, Wimar A. Van den Brink, Michiel Wagemakers, Georg Widhalm, Marnix G. Witte, Aeilko H. Zwinderman, Philip C. De Witt Hamer, Ole Solheim, Ingerid Reinertsen, David Bouget, S. Bakas, C. Sako, H. Akbari, M. Bilello, A. Sotiras, G. Shukla, J. D. Rudie, N. Flores Santamaria, A. Fathi Kazerooni, S. Pati, S. Rathore, E. Mamourian, S. M. Ha, W. Parker, J. Doshi, U. Baid, M. Bergman, Z. A. Binder, R. Verma, R. Lustig, A. S. Desai, S. J. Bagley, Z. Mourelatos, J. Morrissette, C. D. Watt, S. Brem, R. L. Wolf, E. R. Melhem, M. P. Nasrallah, S. Mohan, D. M. O’Rourke, C. Davatzikos
Copyrights: SINTEF, NTNU, St. Olavs Hospital, The Cancer Imaging Archive, SINTEF
Licenses:
CC BY 4.0
BSD 2-Clause