Oncology is a branch of medicine that deals with the prevention, diagnosis, and treatment of cancer.
(definition from Wikipedia)
- Robust breast cancer detection in mammography and digital breast tomosynthesis using annotation-efficient deep learning approach - 2019
- Improved Grading of Prostate Cancer Using Deep Learning - 2018
- Cancer Detection
- Breast Tumour Classification
- Lung Nodule Classification
- Cancer Metastasis Detection
- Prediction of immunotherapy response using deep learning of PET/CT images
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Isic Archive - Melanoma This archive contains 23k images of classified skin lesions. It contains both malignant and benign examples. Each example contains the image of the lesion, meta data regarding the lesion (including clasisfication and segmentation) and meta data regarding the patient.
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Lung Image Database Consortium - The intent of the Lung Imaging Database Consortium (LIDC) initiative was to support a consortium of institutions to develop consensus guidelines for a spiral CT lung image resource and to construct a database of spiral CT lung images.
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CT Colongraphy for Colon Cancer CT scan for diagnosing of colon cancer. Includes data for patients without polyps, 6-9mm polyps, and greater than 10 mm polyps.
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TCIA Collections - Cancer imaging data sets across various cancer types (e.g. carcinoma, lung cancer, myeloma) and various imaging modalities. The image data in The Cancer Imaging Archive (TCIA) is organized into purpose-built collections of subjects. The subjects typically have a cancer type and/or anatomical site (lung, brain, etc.) in common.
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The Mammographic Image Analysis Society (MIAS) mini-database
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Mammography Image Databases 100 or more images of mammograms with ground truth
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INbreast - Database for Digital Mammography
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Multimodal Brain Tumor Segmentation Challenge - Large data set of brain tumor magnetic resonance scans. They’ve been extending this data set and challenge each year since 2012.
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Coding4Cancer- A new initiative by the Foundation for the National Institutes of Health and Sage Bionetworks to host a series of challenges to improve cancer screening. The first is for digital mammography readings. The second is for lung cancer detection. The challenges are not yet launched.
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2019 Kidney and Kidney Tumor Segmentation Challenge (KiTS19)
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Evaluation of Embeddings of Laboratory Test Codes for Patients at a Cancer Center
- Histopathologic Cancer Detection: identify metastatic tissue in histopathologic scans of lymph node sections - Kaggle - 2019
- Data Science Bowl 2017: Can you improve lung cancer detection? - Kaggle - 2017
- Intel & MobileODT Cervical Cancer Screening: which cancer treatment will be most effective? - Kaggle - 2017
- Personalized Medicine: redefining cancer treatment - Kaggle - 2017