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As part of the Small Animal/Co-clinical Improved DICOM Compliance and Data Integration sub-project of CTIIP, the NCI commissioned supported the development of a DICOM supplement for small animal imaging. The group of people contributing to it, Working Group 30, completed Supplement 187: Preclinical Small Animal Imaging Acquisition Context
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Consult Supplement 187: Preclinical Small Animal Imaging Acquisition Context
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Challenges are being increasingly viewed as a mechanism to foster advances in a number of fields, including healthcare and medicine. Large quantities of publicly available data, such as TCIA, and cultural changes in the openness of science have now made it possible to use these challenges, as well as crowdsourcing (enlisting the services of people via the Internet), to propel the field forward.
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The Pilot Challenges sub-project of CTIIP will make a set of integrated data from TCIA and TCGA publicly available to researchers who will participate in three complementary "pilot challenge" projects. (this only happened in the first challenge to figure out which image was from which tumor–look at Miccai ) These pilot challenges proactively address research questions that compare the decision support systems for clinical imaging, co-clinical imaging, and digital pathology. As opposed to a more rigorous "grand" challenge, each pilot challenge will function as a proof of concept to learn how to scale challenges up in the future. Each challenge will use the informatics infrastructure created in the Digital Pathology and Integrated Query System sub-project and allow participants to validate and share algorithms on a software clearinghouse platform such as HUBZero.
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The pilot challenges are as follows:
| MICCAI 2015 Challenges | Description |
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| Combined Radiology and Pathology Classification | |
| Segmentation of Nuclei in Pathology Images | |
| Discipline | Pilot Challenge |
| Clinical Imaging | Pilot challenge projects are being explored for X-ray CT, DWI MRI and PET CT similar to the HUBzero pilot CT challenge project. |
| Pre-clinical / Co-clinical Imaging | Leverage the Mouse Models of Human Cancer Consortium (MHHCC) Glioblastoma co-clinical trials with associated omics data sets from the Human Brain Consortium. This proof-of-concept will focus on bringing together omics and imaging data into a single platform. |
| Digital Pathology | Develop open source image analysis algorithms that complement omics data sets and provide additional decision support.
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