762 citations · 833 across the 28 of their papers we have counts for
12 papers · 1 filter
Fully Automated Deep Learning Based Glenoid Bone Loss Measurement and Severity Stratification on 3D CT in Shoulder Instability
Zhonghao Liu, Hanxue Gu, Qihang Li +4
To develop and validate a fully automated, deep-learning pipeline for measuring glenoid bone loss on 3D CT scans using linear-based, en-face view, and best-circle method. Shoulder…
SAMora: Enhancing SAM through Hierarchical Self-Supervised Pre-Training for Medical Images
Shuhang Chen, Hangjie Yuan, Pengwei Liu +3
The Segment Anything Model (SAM) has demonstrated significant potential in medical image segmentation. Yet, its performance is limited when only a small amount of labeled data is a…
Transplant-Ready? Evaluating AI Lung Segmentation Models in Candidates with Severe Lung Disease
Jisoo Lee, Michael R. Harowicz, Yuwen Chen +5
This study evaluates publicly available deep-learning based lung segmentation models in transplant-eligible patients to determine their performance across disease severity levels,…
Are Vision Foundation Models Ready for Out-of-the-Box Medical Image Registration?
Hanxue Gu, Yaqian Chen, Nicholas Konz +2
Foundation models, pre-trained on large image datasets and capable of capturing rich feature representations, have recently shown potential for zero-shot image registration. Howeve…
MRI-CORE: A Foundation Model for Magnetic Resonance Imaging
Haoyu Dong, Yuwen Chen, Hanxue Gu +4
The widespread use of Magnetic Resonance Imaging (MRI) in combination with deep learning shows promise for many high-impact automated diagnostic and prognostic tools. However, trai…
BreastSegNet: Multi-label Segmentation of Breast MRI
Qihang Li, Jichen Yang, Yaqian Chen +4
Breast MRI provides high-resolution imaging critical for breast cancer screening and preoperative staging. However, existing segmentation methods for breast MRI remain limited in s…
Improving Surgical Risk Prediction Through Integrating Automated Body Composition Analysis: a Retrospective Trial on Colectomy Surgery
Hanxue Gu, Yaqian Chen, Jisoo Lee +5
Objective: To evaluate whether preoperative body composition metrics automatically extracted from CT scans can predict postoperative outcomes after colectomy, either alone or combi…
SegmentAnyMuscle: A universal muscle segmentation model across different locations in MRI
Roy Colglazier, Jisoo Lee, Haoyu Dong +12
The quantity and quality of muscles are increasingly recognized as important predictors of health outcomes. While MRI offers a valuable modality for such assessments, obtaining pre…
GuidedMorph: Two-Stage Deformable Registration for Breast MRI
Yaqian Chen, Hanxue Gu, Haoyu Dong +5
Accurately registering breast MR images from different time points enables the alignment of anatomical structures and tracking of tumor progression, supporting more effective breas…
Accelerating Volumetric Medical Image Annotation via Short-Long Memory SAM 2
Yuwen Chen, Zafer Yildiz, Qihang Li +5
Manual annotation of volumetric medical images, such as magnetic resonance imaging (MRI) and computed tomography (CT), is a labor-intensive and time-consuming process. Recent advan…
Breast density in MRI: an AI-based quantification and relationship to assessment in mammography
Yaqian Chen, Lin Li, Hanxue Gu +5
Mammographic breast density is a well-established risk factor for breast cancer. Recently there has been interest in breast MRI as an adjunct to mammography, as this modality provi…
Automated Muscle and Fat Segmentation in Computed Tomography for Comprehensive Body Composition Analysis
Yaqian Chen, Hanxue Gu, Yuwen Chen +7
Body composition assessment using CT images can potentially be used for a number of clinical applications, including the prognostication of cardiovascular outcomes, evaluation of m…