Semi automatically generated nuclei instance segmentation and classification dataset with exhaustive nuclei labels across 19 different tissue types. The dataset consists of 481 visual fields, of which 312 are randomly sampled from more than 20K whole slide images at different magnifications, from multiple data sources. In total the dataset contains 205,343 labeled nuclei, each with an instance segmentation mask. Models trained on pannuke can aid in whole slide image tissue type segmentation, and generalise to new tissues. PanNuke demonstrates one of the first succesfully semi-automatically generated datasets.
Subscribe to:
Post Comments (Atom)
Popular Posts
-
코퍼스 명 용도 설명 링크 Naver sentiment movie corpus v1.0 분류 네이버 영화 리뷰 ( 긍정 , 부정 ) 분류 라벨링 됨 https://github.com/e9t/nsmc C...
-
This data set was created to understand the potential for machine learning, computer vision, and HPC to improve the energy efficiency aspec...
-
https://metatext.io/datasets-list/finnish-language FI News Corpus Dataset is a collection of news headlines and short summaries of text, o...
-
Natural-Image Datasets MNIST: handwritten digits : The most commonly used sanity check. Dataset of 25x25, centered, B&W handwritten d...
-
Stanford Background Dataset Sift Flow Dataset Barcelona Dataset Microsoft COCO dataset MSRC Dataset LITS Liver Tumor Segmentation Data...
-
Text Datasets 20 newsgroups : Classification task, mapping word occurences to newsgroup ID. One of the classic datasets for text classifi...

No comments:
Post a Comment