Huihui Wang

Beijing, China

Last Updated: 09/26/2026

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Found 16 publications

Integrating 3D Volumetric Segmentation and LLM-Based Classification for csPCa Detection on mpMRI: Multi-Institutional External Validation.

Integrating 3D Volumetric Segmentation and LLM-Based Classification for csPCa Detection on mpMRI: Multi-Institutional External Validation.

Journal: Academic radiology

Published: March 04, 2026

An AI-Based Radiomics Model Using MRI ADC Maps for Accurate Prediction of Advanced Prostate Cancer Progression.

An AI-Based Radiomics Model Using MRI ADC Maps for Accurate Prediction of Advanced Prostate Cancer Progression.

Journal: Current oncology (Toronto, Ont.)

Published: December 01, 2025

Assessing the Performance of Artificial Intelligence Assistance for Prostate MRI: A Two-Center Study Involving Radiologists With Different Experience Levels.

Assessing the Performance of Artificial Intelligence Assistance for Prostate MRI: A Two-Center Study Involving Radiologists With Different Experience Levels.

Journal: Journal of magnetic resonance imaging : JMRI

Published: March 26, 2024

Deep learning-based radiomics model from pretreatment ADC to predict biochemical recurrence in advanced prostate cancer.

Deep learning-based radiomics model from pretreatment ADC to predict biochemical recurrence in advanced prostate cancer.

Journal: Frontiers in oncology

Published: November 21, 2023

Deep learning-based fully automated detection and segmentation of pelvic lymph nodes on diffusion-weighted images for prostate cancer: a multicenter study.

Deep learning-based fully automated detection and segmentation of pelvic lymph nodes on diffusion-weighted images for prostate cancer: a multicenter study.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society

Published: May 22, 2023

Investigation of radiomics models for predicting biochemical recurrence of advanced prostate cancer on pretreatment MR ADC maps based on automatic image segmentation.

Investigation of radiomics models for predicting biochemical recurrence of advanced prostate cancer on pretreatment MR ADC maps based on automatic image segmentation.

Journal: Journal of applied clinical medical physics

Published: May 10, 2023

Deep-Learning Models for Detection and Localization of Visible Clinically Significant Prostate Cancer on Multi-Parametric MRI.

Deep-Learning Models for Detection and Localization of Visible Clinically Significant Prostate Cancer on Multi-Parametric MRI.

Journal: Journal of magnetic resonance imaging : JMRI

Published: November 01, 2022

Preoperative Prediction of Extracapsular Extension: Radiomics Signature Based on Magnetic Resonance Imaging to Stage Prostate Cancer.

Preoperative Prediction of Extracapsular Extension: Radiomics Signature Based on Magnetic Resonance Imaging to Stage Prostate Cancer.

Journal: Molecular imaging and biology

Published: July 20, 2019

MRI-Based Radiomics Signature for the Preoperative Prediction of Extracapsular Extension of Prostate Cancer.

MRI-Based Radiomics Signature for the Preoperative Prediction of Extracapsular Extension of Prostate Cancer.

Journal: Journal of magnetic resonance imaging : JMRI

Published: March 20, 2019

Preoperative PI-RADS Version 2 scores helps improve accuracy of clinical nomograms for predicting pelvic lymph node metastasis at radical prostatectomy.

Preoperative PI-RADS Version 2 scores helps improve accuracy of clinical nomograms for predicting pelvic lymph node metastasis at radical prostatectomy.

Journal: Prostate cancer and prostatic diseases

Published: January 17, 2019

Diagnostic efficacy of b value (2000 s/mm2) diffusion-weighted imaging for prostate cancer: Comparison of a reduced field of view sequence and a conventional technique.

Diagnostic efficacy of b value (2000 s/mm2) diffusion-weighted imaging for prostate cancer: Comparison of a reduced field of view sequence and a conventional technique.

Journal: European journal of radiology

Published: July 07, 2018

Contemporary Epstein Criteria with Biopsy-Naïve Multiparametric Magnetic Resonance Imaging to Prevent Incorrect Assignment to Active Surveillance in the PI-RADS Version 2.0 Era.

Contemporary Epstein Criteria with Biopsy-Naïve Multiparametric Magnetic Resonance Imaging to Prevent Incorrect Assignment to Active Surveillance in the PI-RADS Version 2.0 Era.

Journal: Annals of surgical oncology

Published: April 30, 2018

Showing 1-12 of 16

Last Updated: 09/26/2026