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Towards Generation, Management, and Exploration of Combined Radiomics and Pathomics Datasets for Cancer Research

Authors :
Saltz, Joel
Almeida, Jonas
Gao, Yi
Sharma, Ashish
Bremer, Erich
DiPrima, Tammy
Saltz, Mary
Kalpathy-Cramer, Jayashree
Kurc, Tahsin
Source :
AMIA Summits on Translational Science Proceedings
Publication Year :
2017
Publisher :
American Medical Informatics Association, 2017.

Abstract

Cancer is a complex multifactorial disease state and the ability to anticipate and steer treatment results will require information synthesis across multiple scales from the host to the molecular level. Radiomics and Pathomics, where image features are extracted from routine diagnostic Radiology and Pathology studies, are also evolving as valuable diagnostic and prognostic indicators in cancer. This information explosion provides new opportunities for integrated, multi-scale investigation of cancer, but also mandates a need to build systematic and integrated approaches to manage, query and mine combined Radiomics and Pathomics data. In this paper, we describe a suite of tools and web-based applications towards building a comprehensive framework to support the generation, management and interrogation of large volumes of Radiomics and Pathomics feature sets and the investigation of correlations between image features, molecular data, and clinical outcome.

Subjects

Subjects :
Articles

Details

Language :
English
ISSN :
21534063
Volume :
2017
Database :
OpenAIRE
Journal :
AMIA Summits on Translational Science Proceedings
Accession number :
edsair.pmid..........32899b57443bd7e6eb022e9271672c3d