154 citations · 210 across the 6 of their papers we have counts for
7 papers
The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue
Philippe Weitz, Masi Valkonen, Leslie Solorzano +38
The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications. Advances in computing, deep learning, and availability…
Deep Learning based Prediction of MSI using MMR Markers in Colorectal Cancer
Ruqayya Awan, Mohammed Nimir, Shan E Ahmed Raza +5
The accurate diagnosis and molecular profiling of colorectal cancers are critical for planning the best treatment options for patients. Microsatellite instability (MSI) or mismatch…
Deep Feature based Cross-slide Registration
Ruqayya Awan, Shan E Ahmed Raza, Johannes Lotz +2
Cross-slide image analysis provides additional information by analysing the expression of different biomarkers as compared to a single slide analysis. These biomarker stained slide…
Comparison of Consecutive and Re-stained Sections for Image Registration in Histopathology
Johannes Lotz, Nick Weiss, Jeroen van der Laak +1
Purpose: In digital histopathology, virtual multi-staining is important for diagnosis and biomarker research. Additionally, it provides accurate ground-truth for various deep-learn…
Virtual staining for mitosis detection in Breast Histopathology
Caner Mercan, Germonda Reijnen-Mooij, David Tellez Martin +4
We propose a virtual staining methodology based on Generative Adversarial Networks to map histopathology images of breast cancer tissue from H&E stain to PHH3 and vice versa. We us…
Robust, fast and accurate: a 3-step method for automatic histological image registration
Johannes Lotz, Nick Weiss, Stefan Heldmann
We present a 3-step registration pipeline for differently stained histological serial sections that consists of 1) a robust pre-alignment, 2) a parametric registration computed on…
Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard
Wouter Bulten, Péter Bándi, Jeffrey Hoven +7
Prostate cancer (PCa) is graded by pathologists by examining the architectural pattern of cancerous epithelial tissue on hematoxylin and eosin (H&E) stained slides. Given the impor…