SAFRON: Stitching Across the Frontier Network for Generating Colorectal Cancer Histology Images
- 1 April 2022
- journal article
- research article
- Published by Elsevier in Medical Image Analysis
- Vol. 77, 102337
Abstract
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Funding Information
- UK Research and Innovation
- Medical Research Council (MR/P015476/1)
- Alan Turing Institute
This publication has 25 references indexed in Scilit:
- Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology imagesJournal of Medical Imaging, 2017
- Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast CancerJAMA, 2017
- Glandular Morphometrics for Objective Grading of Colorectal Adenocarcinoma Histology ImagesScientific Reports, 2017
- DCAN: Deep contour-aware networks for object instance segmentation from histology imagesMedical Image Analysis, 2017
- Gland segmentation in colon histology images: The glas challenge contestMedical Image Analysis, 2017
- A model of the spatial tumour heterogeneity in colorectal adenocarcinoma tissueBMC Bioinformatics, 2016
- A Stochastic Polygons Model for Glandular Structures in Colon Histology ImagesIEEE Transactions on Medical Imaging, 2015
- SimuCell: a flexible framework for creating synthetic microscopy imagesNature Methods, 2012
- Medical Education Research As Translational ScienceScience Translational Medicine, 2010
- Statistical validation of image segmentation quality based on a spatial overlap index1Academic Radiology, 2004