AUTHOR=Wu Jiaojiao , Xia Yuwei , Wang Xuechun , Wei Ying , Liu Aie , Innanje Arun , Zheng Meng , Chen Lei , Shi Jing , Wang Liye , Zhan Yiqiang , Zhou Xiang Sean , Xue Zhong , Shi Feng , Shen Dinggang TITLE=uRP: An integrated research platform for one-stop analysis of medical images JOURNAL=Frontiers in Radiology VOLUME=3 YEAR=2023 URL=https://www.frontiersin.org/journals/radiology/articles/10.3389/fradi.2023.1153784 DOI=10.3389/fradi.2023.1153784 ISSN=2673-8740 ABSTRACT=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.