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• Breast Image Feature Scoring Project - This project is in the preliminary stages and is being collaborated on by group members from MSKCC, MDACC, Roswell Park, and UPMC.  Multiple readers are evaluating each subject's imaging features using a BIRADS inspired Breast Feature Key and then investigating potential correlations with the TCGA genomic and clinical data.  This project is being led by Liz Morris of MSKCC.
• Mapping of Multi-modality Breast Image-based Phenotypes to Histopathology and Genomics – This project seeks to advance and relate quantitative, computer-extracted tumor and parenchymal characteristics from multi-modality breast images (e.g, mammography, ultrasound, and MRI) to clinical outcomes (diagnosis, staging, and response to therapy), histopathology, and genomics.  This project is led by Maryellen Giger (University of Chicago), and TBN others.  The quantitative output from this project feeds other projects such as the Breast Image Feature Scoring Project.
• Correlating computer-extracted MRI features with clinical and genomic data - In this project, features are extracted from breast MR images using computer vision algorithms. These features are then correlated with clinical and genomic information. This project is being led by Maciej Mazurowski from Duke University.
• Clustering (supervised & unsupervised) of BRCA Data - Cases are clustered into semantically-distinct categories using image-derived features, followed by examination of genomic correlates from the obtained clusters.  This project is being led by Arvind Rao and Gary Whitman of MDACC.

Publications

There are currently no imaging based publications for TCGA-BRCA. However, the following links contain publications from the main TCGA project, as well as their posted publication guidelines.

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