Research Publications
Pioneering research in medical imaging AI and kidney volume estimation
Improved predictions of total kidney volume growth rate in ADPKD using two-parameter least squares fitting
Authors: Zhongxiu Hu, Arman Sharbatdaran, Xinzi He, Chenglin Zhu, Jon D. Blumenfeld, Hanna Rennert, Zhengmao Zhang, Andrew Ramnauth, Daniil Shimonov, James M. Chevalier, Martin R. Prince
Journal: Scientific Reports
Publication Date: June 14, 2024
The Role of Baseline Total Kidney Volume Growth Rate in Predicting Tolvaptan Efficacy for ADPKD Patients: A Feasibility Study
Authors: Hreedi Dev, Zhongxiu Hu, Jon D. Blumenfeld, Arman Sharbatdaran, Yelynn Kim, Chenglin Zhu, Daniil Shimonov, James M. Chevalier, Stephanie Donahue, Alan Wu, Arindam RoyChoudhury, Xinzi He, Martin R. Prince
Journal: Journal of Clinical Medicine
Publication Date: February 21, 2025
Deep learning-based liver cyst segmentation in MRI for autosomal dominant polycystic kidney disease
Authors: Mina Chookhachizadeh Moghadam, Mohit Aspal, Xinzi He, Dominick J Romano, Arman Sharbatdaran, Zhongxiu Hu, Kurt Teichman, Hui Yi Ng He, Usama Sattar, Chenglin Zhu, Hreedi Dev, Daniil Shimonov, James M Chevalier, Akshay Goel, George Shih, Jon D Blumenfeld, Mert R Sabuncu, Martin R Prince
Journal: Radiology Advances
Publication Date: May 23, 2024
Automatically Detecting Pancreatic Cysts in Autosomal Dominant Polycystic Kidney Disease on MRI Using Deep Learning
Authors: Sophia J. Wang, Zhongxiu Hu, Cathy Li, Xinzi He, Chenglin Zhu, Yaoyao Wang, Usama Sattar, Vignesh Bazojoo, Hui Yi Ng He, Jon D. Blumenfeld, Martin R. Prince
Journal: Tomography
Publication Date: July 2024
Research Impact
Our research has made significant contributions to the field of medical imaging AI, particularly in:
- Advanced algorithms for kidney volume estimation in ADPKD patients
- Novel approaches to predict disease progression and treatment efficacy
- Privacy-preserving methods for medical image analysis
- Integration of AI models into clinical workflows