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6 research data, page 1 of 1

Variations of dynamic contrast-enhanced magnetic resonance imaging in evaluation of breast cancer therapy response: a multicenter data analysis challenge

This collection of breast dynamic contrast-enhanced (DCE) MRI data contains images from a longitudinal study to assess breast cancer response to neoadjuvant chemotherapy. Images were acquired at four time points: prior to the start of treatment (Visit 1, V1), after the first cycle of treatment (Visit 2, V2), at midpoint of treatment course (Visit 3, V3), and after completion of treatment (prior to surgery) (Visit 4, V4). The value of this collection is to provide clinical imaging data for the...

Curated Breast Imaging Subset of DDSM

Sawyer-Lee, Rebecca; Gimenez, Francisco; Hoogi, Assaf; Rubin, Daniel (2016)
Publisher: The Cancer Imaging Archive
This CBIS-DDSM (Curated Breast Imaging Subset of DDSM) is an updated and standardized version of the Digital Database for Screening Mammography (DDSM). The DDSM is a database of 2,620 scanned film mammography studies. It contains normal, benign, and malignant cases with verified pathology information. The scale of the database along with ground truth validation makes the DDSM a useful tool in the development and testing of decision support systems. The CBIS-DDSM collection includes a subset ...

Data From LIDC-IDRI

The Lung Image Database Consortium image collection (LIDC-IDRI) consists of diagnostic and lung cancer screening thoracic computed tomography (CT) scans with marked-up annotated lesions. It is a web-accessible international resource for development, training, and evaluation of computer-assisted diagnostic (CAD) methods for lung cancer detection and diagnosis. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and ...

Data From REMBRANDT

Scarpace, Lisa; Flanders, Adam E.; Jain, Rajan; Mikkelsen, Tom; Andrews, David W. (2015)
Publisher: The Cancer Imaging Archive
Finding better therapies for the treatment of brain tumors is hampered by the lack of consistently obtained molecular data in a large sample set and the ability to integrate biomedical data from disparate sources enabling translation of therapies from bench to bedside. Hence, a critical factor in the advancement of biomedical research and clinical translation is the ease with which data can be integrated, redistributed, and analyzed both within and across functional domains. Novel biomedical ...