ArticleFrontiers in radiology2023
uRP: An integrated research platform for one-stop analysis of medical images.
Article in Frontiers in radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 111 papers.
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Who cites it
111 citing papers in PubMed.
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- Intratumoral and peritumoral CT radiomics combined with clinical and hematologic inflammatory markers for predicting lymph node metastasis in esophageal squamous cell carcinoma: a retrospective single-center study.La Radiologia medica · 2026Article
- A Noninvasive Circulating Tumor DNA Methylation Classifier to Identify Benign Pulmonary Nodules.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Article
- Comparison of Thrombocytopenia and Splenomegaly in Locally Advanced Rectal Cancer Patients Receiving Total Neoadjuvant Therapy With and Without Immunotherapy.Cancer medicine · 2026Article
- Deep learning-assisted tumor radiomic dynamics on MRI predict pathological complete response in HCC undergoing immune-based therapy followed by hepatectomy.Hepatology (Baltimore, Md.) · 2026Article
- Predicting placenta accreta spectrum antenatally: a deep learning-radiomics dual-model based on intraoperative clinical and histopathologic criteria.BMC medical imaging · 2026Article
- GAN-generated target reconstruction CT radiomics for prediction of the novel IASLC grading of pulmonary adenocarcinoma.Journal of thoracic disease · 2026Article
- Radiomics-enhancedEuropean radiology experimental · 2026Article
- An interpretable radiomics-machine learning model for early risk stratification of invasive fungal infections in community-acquired pneumonia: a dual-center study.Scientific reports · 2026Article
- [Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Predicting pulmonary nodule growth from a single time point: a fusion model of radiomics and deep learning to optimize follow-up strategies.Journal of thoracic disease · 2026Article
- Monitoring pneumonia onset and severe respiratory infectious diseases using quantitative computed tomography, validation amidst the coronavirus disease 2019 outbreak at the end of 2022 in the Chinese mainland.Journal of thoracic disease · 2026Article
- Application of a multimodal MRI model integrating radiomics and habitat features for predicting glioma pathology and prognosis.BMC medical imaging · 2026Article
- Altered glymphatic-related MRI markers in children with acute lymphoblastic and myeloid leukemia at diagnosis.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Multicenter development and external validation of clinical-radiomics models to predict surgically confirmed upstaging in biopsy-proven DCIS using DCE-MRI.Journal of applied clinical medical physics · 2026Article
- Improving risk stratification of pulmonary nodules: an integrated perinodular vascular and radiomic model for clinical decision support.BMC medical imaging · 2026Article
- Prognostic value of cardiac fibroblast activation heterogeneity assessed by FAPI PET radiomics in hypertrophic cardiomyopathy: a proof-of-concept study.Open heart · 2026Article
- Association of the along‑perivascular space (ALPS) index and white matter volume with cognitive dysfunction in relapsing‑remitting multiple sclerosis patients.BMC neurology · 2026Article
51 more citing papers are in PubMed but not listed here.
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15 authors.
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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.
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