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期刊名:Abdominal radiology

缩写:ABDOM RADIOL

ISSN:2366-004X

e-ISSN:2366-0058

IF/分区:2.2/Q2

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Clinical Trial Case Reports Meta-Analysis RCT Review Systematic Review
Classical Article Case Reports Clinical Study Clinical Trial Clinical Trial Protocol Comment Comparative Study Editorial Guideline Letter Meta-Analysis Multicenter Study Observational Study Randomized Controlled Trial Review Systematic Review
Gouling Zhan,Zuoxi Li,Xuehuan Liu et al. Gouling Zhan et al.
Objectives: Accurate prediction of response to first-line oxaliplatin-based chemotherapy in unresectable colorectal liver metastases (CRLM) is critical for optimizing treatment strategies. This study aimed to develop and ...
Ahmed Faisal Mutee,Ali Fawzi Al-Hussainy,Nathier A Ibrahim et al. Ahmed Faisal Mutee et al.
Objective: To develop and evaluate a comprehensive AI-driven pipeline for automated segmentation and multi-class classification of ovarian tumors in ultrasound images using advanced transformer-based models and radiomic a...
Bin Li,Jian Zhang,Hao Fu et al. Bin Li et al.
Objectives: This study aims to automate segmentation of the biliary and pancreatic systems on 3D negative-contrast CT cholangiopancreatography (3D-nCTCP) to improve preoperative planning and diagnosis. ...
Linda Le,Luke A Ginocchio,Sooah Kim et al. Linda Le et al.
Purpose: Pancreatic cystic lesions (PCL) commonly undergo surveillance using MRI with MR cholangiopancreatography (MRCP). Our objective is to compare the performance of a single-shot fat-saturated T2-weighted technique wi...
Yingxue Tong,Haoru Wang,Xiangmin Zhang et al. Yingxue Tong et al.
Purpose: To preliminarily evaluate the predictive value of baseline contrast-enhanced CT (CECT) radiomics for assessing chemotherapy response in pediatric lymphoma. ...
Zhou Lu,Siwei Zhang,Zekai Wang et al. Zhou Lu et al.
Objective: To evaluate the added value of intratumoral and peritumoral radiomic scores (RS) of iodine density (IoD) map in the preoperative prediction of lymphovascular invasion (LVI) in gastric adenocarcinoma. ...
Lindsey H Bloom,Tejas Sudharshan Mathai,Bohan Liu et al. Lindsey H Bloom et al.
Objectives: The performance of fully automated deep learning-based models for the detection and segmentation of lymph nodes (LNs) on full- and simulated reduced-dose CT was validated. ...
Mayur Virarkar,Sanaz Javadi,Aatiqah Aziz et al. Mayur Virarkar et al.
Aim: To compare the diagnostic performance of PET/MRI versus PET/CT for lymph node and metastatic disease detection in patients with gynecologic cancers, and to assess whether PET/MRI offers improved staging accuracy and ...
Hao Li,Yuanyuan Fan,Yipu Li et al. Hao Li et al.
Purpose: To develop an integrated predictive model combining radiomics, clinical risk factors, and machine learning for prognostic assessment in hepatocellular carcinoma (HCC) patients receiving continued transarterial ch...