activity
20202024
most citedA Deep Learning-Based Method for Automatic Segmentation of Proximal Femur from Quantitative Computed Tomography Images

7 citations · 14 across the 5 of their papers we have counts for

collaborators

6 papers

physics.med-ph2024

A Staged Approach using Machine Learning and Uncertainty Quantification to Predict the Risk of Hip Fracture

Anjum Shaik, Kristoffer Larsen, Nancy E. Lane +8

Despite advancements in medical care, hip fractures impose a significant burden on individuals and healthcare systems. This paper focuses on the prediction of hip fracture risk in…

cs.LG20221 cited

A New Hip Fracture Risk Index Derived from FEA-Computed Proximal Femur Fracture Loads and Energies-to-Failure

Xuewei Cao, Joyce H Keyak, Sigurdur Sigurdsson +7

Hip fracture risk assessment is an important but challenging task. Quantitative CT-based patient specific finite element analysis (FEA) computes the force (fracture load) to break…

stat.ML20224 cited

A robust kernel machine regression towards biomarker selection in multi-omics datasets of osteoporosis for drug discovery

Md Ashad Alam, Hui Shen, Hong-Wen Deng

Many statistical machine approaches could ultimately highlight novel features of the etiology of complex diseases by analyzing multi-omics data. However, they are sensitive to some…

cs.CV2021

A Deep Learning-Based Approach to Extracting Periosteal and Endosteal Contours of Proximal Femur in Quantitative CT Images

Yu Deng, Ling Wang, Chen Zhao +4

Automatic CT segmentation of proximal femur is crucial for the diagnosis and risk stratification of orthopedic diseases; however, current methods for the femur CT segmentation main…

eess.IV20212 cited

A new approach to extracting coronary arteries and detecting stenosis in invasive coronary angiograms

Chen Zhao, Haipeng Tang, Daniel McGonigle +6

In stable coronary artery disease (CAD), reduction in mortality and/or myocardial infarction with revascularization over medical therapy has not been reliably achieved. Coronary ar…

physics.med-ph20207 cited

A Deep Learning-Based Method for Automatic Segmentation of Proximal Femur from Quantitative Computed Tomography Images

Chen Zhao, Joyce H. Keyak, Jinshan Tang +10

Purpose: Proximal femur image analyses based on quantitative computed tomography (QCT) provide a method to quantify the bone density and evaluate osteoporosis and risk of fracture.…