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Found 6 papers, 1 papers with code
The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue
The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications.
Deep Feature based Cross-slide Registration
During the slide preparation, a tissue section may be placed at an arbitrary orientation as compared to other sections of the same tissue block.
Comparison of Consecutive and Re-stained Sections for Image Registration in Histopathology
Between re-stained sections, the median registration error is 2. 3 {\mu}m and 0. 9 {\mu}m in the two subsets of the HyReCo dataset.
Virtual staining for mitosis detection in Breast Histopathology
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.
Robust, fast and accurate: a 3-step method for automatic histological image registration
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 coarse resolution images, and 3) an accurate nonlinear registration.
Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard
The H&E slides were co-registered to the IHC slides.
