20 datasets found

The dataset is used for digital pathology and contains histology data from various sources.

The dataset is used for digital pathology and contains histology data from various sources.

A large cohort of annotated Hematoxylin & Eosin (H&E)-stained images to advance the characterization of breast lesions.

OpenHI2 is an open-source histopathological image platform that supports basic pathological tasks and file formats.

The Atlas of Digital Pathology (ADP) dataset is a collection of histopathological images from different organs, annotated at the patch level.

The dataset used in this paper consists of whole slide images from five different medical centers, digitized with three different scanners.

The CAMELYON 17 Challenge dataset consists of whole slide images originating from five different medical centers, digitized with three different scanners.

Whole Slide Images (WSIs) of patients from a public hospital pathology service in Western Australia

The dataset used in the paper for whole slide image (WSI) classification, which is a type of digital pathology. The dataset consists of histopathology and cytopathology images,...

The MoNuSeg dataset is published for the Multi-organ Nuclei Segmentation challenge in MICCAI 2018. The training dataset consists of 30 images generated from multiple organs...

Hematoxylin and eosin-stained whole-slide images from Molecular and Cellular Oncology and The Cancer Genome Atlas were used as training and external validation datasets.

A dataset of 624 whole slide images (WSIs) of breast cancer from a Norwegian cohort.

The Norwegian Lung Cancer Biobank (NLCB) cohort and the Bergen cohort were used to create the proposed model. The NLCB cohort includes histopathological, cytological, biomarker,...

The Norwegian Lung Cancer Biobank (NLCB) cohort and the Bergen cohort were used to create the proposed model. The NLCB cohort includes histopathological, cytological, biomarker,...

The dataset used for mitosis detection in breast cancer histology images with deep neural networks.

The dataset used for automatic glandular and tubule region segmentation in histological grading of breast cancer.

The dataset used for tubule segmentation of inhomogeneity images based on convolutional neural networks with fluorescence microscopy correction.

The dataset used for invasive ductal carcinoma detection in whole slide images.

The dataset used for lymphoma classification, IDC detection, nuclei segmentation, epithelium segmentation, tubule segmentation, lymphocyte detection, and mitosis detection.

A custom pipeline (histo-fetch) to efficiently extract random patches and labels from pathology whole slide images (WSIs) for input to a neural network on-the-fly.