Yangdi Wang

发表

Intestinal fibrosis classification in patients with Crohn’s disease using CT enterography–based deep learning: comparisons with radiomics and radiologists

Minhu Chen, Yikai Xu, Zi-Ping Li, 2022, European Radiology.

A Type I Collagen-Targeted MR Imaging Probe for Staging Fibrosis in Crohn’s Disease

Zi-Ping Li, S. Feng, R. Mao, 2021, Frontiers in Molecular Biosciences.

Quantitative Contrast-Enhanced Ultrasound by Sonazoid in the Early Diagnosis of Biliary Atresia: An Experimental Study of Rats With Bile Duct Ligation.

Xiao-yan Xie, Dong Chen, Yu Guo, 2019, Ultrasound in medicine & biology.

Identifying patients with Crohn's disease at high risk of primary nonresponse to infliximab using a radiomic‐clinical model

Minhu Chen, Baili Chen, Zi-Ping Li, 2022, Int. J. Intell. Syst..

A narrative review of multiple endocrine neoplasia syndromes: genetics, clinical features, imaging findings, and diagnosis

Jie Chen, Chenyu Song, Zi-Ping Li, 2021, Annals of translational medicine.

Multi-frequency magnetic resonance elastography of the pancreas: measurement reproducibility and variance among healthy volunteers

S. Feng, Zhi Lin, Zhen-peng Peng, 2022, Gastroenterology report.

Predicting the recurrence risk of pancreatic neuroendocrine neoplasms after radical resection using deep learning radiomics with preoperative computed tomography images

Jie Chen, Chenyu Song, Jingxian Shen, 2021, Annals of translational medicine.

Preoperative computed tomography enterography-based radiomics signature: A potential predictor of postoperative anastomotic recurrence in patients with Crohn's disease.

Jie Zhou, S. Feng, R. Mao, 2023, European journal of radiology.

Inflammatory bowel disease cross‐sectional imaging: What's new?

R. Mao, Xue-hua Li, Yangdi Wang, 2022, United European gastroenterology journal.

Intestinal fibrosis classification in patients with Crohn’s disease using CT enterography–based deep learning: comparisons with radiomics and radiologists

Minhu Chen, Yikai Xu, Bingsheng Huang, 2022, European Radiology.

Optimization of the tumour response threshold in advanced gastroenteropancreatic neuroendocrine carcinomas treated with cisplatin/etoposide combined chemotherapy.

Jie Chen, Chenyu Song, S. Feng, 2021, European journal of radiology.

Clinical outcome is distinct between radiological stricture and endoscopic stricture in ileal Crohn's disease.

S. Feng, Zhen-peng Peng, R. Mao, 2023, European Radiology.

CT-based radiomics signature of visceral adipose tissue for prediction of disease progression in patients with Crohn's disease: A multicentre cohort study

Minhu Chen, E. Cui, Bingsheng Huang, 2022, EClinicalMedicine.

Mesenteric abnormalities play an important role in grading intestinal fibrosis in patients with Crohn’s disease: a computed tomography and clinical marker-based nomogram

Y. Mao, S. Feng, R. Mao, 2022, Therapeutic advances in gastroenterology.

Use of dual-layer spectral detector computed tomography in the diagnosis of pancreatic neuroendocrine neoplasms.

S. Feng, Zhen-peng Peng, Siya Shi, 2022, European journal of radiology.

Utility of Quantitative Metrics from Dual-Layer Spectral-Detector CT for Differentiation of Pancreatic Neuroendocrine Tumor and Neuroendocrine Carcinoma.

Chenyu Song, Zhi Lin, Siya Shi, 2022, AJR. American journal of roentgenology.

Dual-energy CT improves differentiation of non-hypervascular pancreatic neuroendocrine neoplasms from CA 19-9-negative pancreatic ductal adenocarcinomas

Siya Shi, Yangdi Wang, Yanji Luo, 2023, La Radiologia medica.

A novel multidisciplinary machine learning approach based on clinical, imaging, colonoscopy, and pathology features for distinguishing intestinal tuberculosis from Crohn's disease.

Yangdi Wang, Xiaodi Shen, Ruo-Nan Zhang, 2024, Abdominal radiology.

Comparative analysis of [18F]F-FAPI PET/CT, [18F]F-FDG PET/CT and magnetization transfer MR imaging to detect intestinal fibrosis in Crohn's disease: A prospective animal model and human cohort study.

Siyun Huang, Xiangsong Zhang, Xinming Song, 2024, European Journal of Nuclear Medicine and Molecular Imaging.