uRP: An integrated research platform for one-stop analysis of medical images

被引:54
作者
Wu, Jiaojiao [1 ]
Xia, Yuwei [1 ]
Wang, Xuechun [1 ]
Wei, Ying [1 ]
Liu, Aie [1 ]
Innanje, Arun [2 ]
Zheng, Meng [2 ]
Chen, Lei [1 ]
Shi, Jing [1 ]
Wang, Liye [1 ]
Zhan, Yiqiang [1 ]
Zhou, Xiang Sean [1 ]
Xue, Zhong [1 ]
Shi, Feng [1 ]
Shen, Dinggang [1 ,3 ,4 ]
机构
[1] Shanghai United Imaging Intelligence Co Ltd, Dept Res & Dev, Shanghai, Peoples R China
[2] United Imaging Intelligence Co Ltd, Dept Res & Dev, Cambridge, MA USA
[3] ShanghaiTech Univ, Sch Biomed Engn, Shanghai, Peoples R China
[4] Shanghai Clin Res & Trial Ctr, Shanghai, Peoples R China
来源
FRONTIERS IN RADIOLOGY | 2023年 / 3卷
关键词
research platform; one-stop; medical image analysis; deep learning; semi-automatic delineation; radiomics; LEARNING FRAMEWORK; NETWORKS; MRI; PET;
D O I
10.3389/fradi.2023.1153784
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Introduction Medical 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.Methods We 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 Discussion The 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.
引用
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页数:17
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