whole slide images
80 papers with code • 0 benchmarks • 4 datasets
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Hybrid guiding: A multi-resolution refinement approach for semantic segmentation of gigapixel histopathological images
To validate the design, we conducted an ablation study to assess the impact of selected components in the pipeline on tumour segmentation.
The International Symposium on Biomedical Imaging (ISBI) held a grand challenge to evaluate computational systems for the automated detection of metastatic breast cancer in whole slide images of sentinel lymph node biopsies.
Additionally, we evaluated object detection methods on a novel data set of 17 completely annotated cytology whole slide images (WSI) containing 78, 047 hemosiderophages.
In digital pathology, tissue slides are scanned into Whole Slide Images (WSI) and pathologists first screen for diagnostically-relevant Regions of Interest (ROIs) before reviewing them.
The pipeline consists of fully convolutional regression-based nucleus detection, followed by per-cell focus selection, and CNN based classification.
EXACT: A collaboration toolset for algorithm-aided annotation of images with annotation version control
In many research areas, scientific progress is accelerated by multidisciplinary access to image data and their interdisciplinary annotation.
For this study, we created the first open source data-set with 19, 983 annotations of BiNC and 1, 416 annotations of MuNC in 32 histological whole slide images of ccMCT.
Application of deep learning on histopathological whole slide images (WSIs) holds promise of improving diagnostic efficiency and reproducibility but is largely dependent on the ability to write computer code or purchase commercial solutions.
We present a unified framework to predict tumor proliferation scores from breast histopathology whole slide images.