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Lung and Colon Cancer Histopathological Image Dataset (LC25000)

2019·255 Zitationen·arXiv (Cornell University)Open Access
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255

Zitationen

6

Autoren

2019

Jahr

Abstract

The field of Machine Learning, a subset of Artificial Intelligence, has led to remarkable advancements in many areas, including medicine. Machine Learning algorithms require large datasets to train computer models successfully. Although there are medical image datasets available, more image datasets are needed from a variety of medical entities, especially cancer pathology. Even more scarce are ML-ready image datasets. To address this need, we created an image dataset (LC25000) with 25,000 color images in 5 classes. Each class contains 5,000 images of the following histologic entities: colon adenocarcinoma, benign colonic tissue, lung adenocarcinoma, lung squamous cell carcinoma, and benign lung tissue. All images are de-identified, HIPAA compliant, validated, and freely available for download to AI researchers.

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Autoren

Institutionen

Themen

Radiomics and Machine Learning in Medical ImagingAI in cancer detectionArtificial Intelligence in Healthcare and Education
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