21 datasets found

The ANHIR dataset consists of 481 image pairs and is split into 230 training and 251 evaluation pairs. For the training image pairs, both source and target landmarks are...

Autofluorescence images of label-free tissue sample can be used to perform micro-structured and multiplexed virtual staining using a deep neural network.

The Breast Cancer Histopathological Image Classification dataset contains images of breast cancer histopathology.

A dataset used for testing the proposed Deep Feature Learning method for histopathology image classification.

A dataset used for training and testing the proposed Deep Feature Learning method for histopathology image classification.

A dataset composed of 35334 breast histopathology images at zoom x5 (1.76 µm per pixel) distributed amongst 23 imbalanced classes, which include both common tumor and benign...

Whole slide image annotation dataset for selective whole slide image annotation

Whole slide image annotation dataset for selective whole slide image annotation

This dataset is used for nuclei grading of clear cell renal cell carcinoma in histopathological images.

This dataset is used for nuclei instance segmentation on histopathology images. It consists of 30 nuclei images of size 1000 x 1000 with 658 nuclei per image on average.

A dataset used for testing the proposed Deep Feature Learning method for histopathology image classification.

The CATCH dataset is used to test the proposed Style-Extracting Diffusion Models (STEDM) for canine cancer histology image segmentation.

The HER2 dataset is used to test the proposed Style-Extracting Diffusion Models (STEDM) for histopathology image segmentation.

The dataset used in this paper is the TCGA dataset, which contains somatic genomic alterations (SGAs) and differentially expressed genes (DEGs) of 4,468 tumors.

The dataset contains 100 images obtained from tissues of either normal or malignant patient tissues.

CoNSeP dataset consists of 41 H&E stained image tiles, each of size 1000x1000 pixels at 40x objective magnification, with annotations of seven types of nuclei: malignant,...

Histopathology nuclei image analysis tasks, the lack of training data becomes a main bottleneck for the performance of learning-based methods.

PanNuke dataset consists of 6078 H&E tiles, each of size 256x256, covering 19 different tissue types. It was designed for nuclei instance classification and segmentation and...

A dataset of 800 haematoxylin and eosin stained slides from 300 patients suffered from cervix squamous carcinoma.

We present a novel diffusion-based approach to generate synthetic histopathological Whole Slide Images (WSIs) at an unprecedented gigapixel scale.