Damaged Tissue Detection
2 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Damaged Tissue Detection
Most implemented papers
Quantifying the effect of color processing on blood and damaged tissue detection in Whole Slide Images
NeelKanwal/Quantifying-the-effect-of-color-processing-on-blood-and-damaged-tissue-detection
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2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP) 2022
Since blood and damaged tissue have subtle color differences, we assess the impact of color processing methods on the binary classification performance of five well-known architectures.
Equipping Computational Pathology Systems with Artifact Processing Pipelines: A Showcase for Computation and Performance Trade-offs
neelkanwal/equipping-computational-pathology-systems-with-artifact-processing-pipeline
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We developed DL pipelines using two MoEs and two multiclass models of state-of-the-art deep convolutional neural networks (DCNNs) and vision transformers (ViTs).
