whole slide images

122 papers with code • 0 benchmarks • 4 datasets

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Use these libraries to find whole slide images models and implementations

Most implemented papers

PanNuke Dataset Extension, Insights and Baselines

TIA-Lab/PanNuke-metrics 24 Mar 2020

The emerging area of computational pathology (CPath) is ripe ground for the application of deep learning (DL) methods to healthcare due to the sheer volume of raw pixel data in whole-slide images (WSIs) of cancerous tissue slides.

Deep Learning for Identifying Metastatic Breast Cancer

3dimaging/DeepLearningCamelyon 18 Jun 2016

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.

Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides

ChristianMarzahl/EIPH_WSI 12 Aug 2019

Additionally, we evaluated object detection methods on a novel data set of 17 completely annotated cytology whole slide images (WSI) containing 78, 047 hemosiderophages.

HistoSegNet: Semantic Segmentation of Histological Tissue Type in Whole Slide Images

lyndonchan/hsn_v1 ICCV 2019

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.

A Deep Learning based Pipeline for Efficient Oral Cancer Screening on Whole Slide Images

MIDA-group/OralScreen 23 Oct 2019

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

ChristianMarzahl/Exact 30 Apr 2020

In many research areas, scientific progress is accelerated by multidisciplinary access to image data and their interdisciplinary annotation.

Dataset on Bi- and Multi-Nucleated Tumor Cells in Canine Cutaneous Mast Cell Tumors

DeepPathology/CCMCTBiMultinucleated 5 Jan 2021

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.

Code-free development and deployment of deep segmentation models for digital pathology

AICAN-Research/FAST-Pathology 16 Nov 2021

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.

A Pragmatic Machine Learning Approach to Quantify Tumor Infiltrating Lymphocytes in Whole Slide Images

uit-hdl/histology 14 Feb 2022

Our approach is to transfer an open source machine learning method for segmentation and classification of nuclei in H&E slides trained on public data to TIL quantification without manual labeling of our data.

Uncertainty-Informed Deep Learning Models Enable High-Confidence Predictions for Digital Histopathology

jamesdolezal/slideflow 9 Apr 2022

Furthermore, we show that UQ thresholding remains reliable in the setting of domain shift, with accurate high-confidence predictions of adenocarcinoma vs. squamous cell carcinoma for out-of-distribution, non-lung cancer cohorts.