1. uRP: An integrated research platform for one-stop analysis of medical images
- Author
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Jiaojiao Wu, Yuwei Xia, Xuechun Wang, Ying Wei, Aie Liu, Arun Innanje, Meng Zheng, Lei Chen, Jing Shi, Liye Wang, Yiqiang Zhan, Xiang Sean Zhou, Zhong Xue, Feng Shi, and Dinggang Shen
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research platform ,one-stop ,medical image analysis ,deep learning ,semi-automatic delineation ,radiomics ,Medical physics. Medical radiology. Nuclear medicine ,R895-920 - Abstract
IntroductionMedical image analysis is of tremendous importance in serving clinical diagnosis, treatment planning, as well as prognosis assessment. However, the image analysis process usually involves multiple modality-specific software and relies on rigorous manual operations, which is time-consuming and potentially low reproducible.MethodsWe present an integrated platform - uAI Research Portal (uRP), to achieve one-stop analyses of multimodal images such as CT, MRI, and PET for clinical research applications. The proposed uRP adopts a modularized architecture to be multifunctional, extensible, and customizable.Results and DiscussionThe uRP shows 3 advantages, as it 1) spans a wealth of algorithms for image processing including semi-automatic delineation, automatic segmentation, registration, classification, quantitative analysis, and image visualization, to realize a one-stop analytic pipeline, 2) integrates a variety of functional modules, which can be directly applied, combined, or customized for specific application domains, such as brain, pneumonia, and knee joint analyses, 3) enables full-stack analysis of one disease, including diagnosis, treatment planning, and prognosis assessment, as well as full-spectrum coverage for multiple disease applications. With the continuous development and inclusion of advanced algorithms, we expect this platform to largely simplify the clinical scientific research process and promote more and better discoveries.
- Published
- 2023
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