Clustering On Image Boundary Regions for Deformable Model Segmentation. - Joshua Stough; Stephen M. Pizer; Edward L. Chaney; Manjari Rao (ISBI, 2004)

Histogram Statistics of Local Model-Relative Image Regions. - Robert E. Broadhurst; Joshua Stough; Stephen M. Pizer; Edward L. Chaney (DSSCV, 2005)

Deep Structure of Images in Populations Via Geometric Models in Populations. - Stephen M. Pizer; Ja-Yeon Jeong; Robert E. Broadhurst; Sean Ho; Joshua Stough (DSSCV, 2005)

A statistical appearance model based on intensity quantile histograms. - Robert E. Broadhurst; Joshua Stough; Stephen M. Pizer; Edward L. Chaney (ISBI, 2006)

Regional Appearance in Deformable Model Segmentation. - Joshua Stough; Robert E. Broadhurst; Stephen M. Pizer; Edward L. Chaney (IPMI, 2007)

Clustering on Local Appearance for Deformable Model Segmentation. - Joshua Stough; Robert E. Broadhurst; Stephen M. Pizer; Edward L. Chaney (ISBI, 2007)

Conditional-mean initialization using neighboring objects in deformable model segmentation. - Ja-Yeon Jeong; Joshua V. Stough; James Stephen Marron; Stephen M. Pizer (Image Processing, 2008)

Clustering and Shifting of Regional Appearance for Deformable Model Segmentation. - Joshua V. Stough (2008)

Thalamic parcellation from multi-modal data using random forest learning. - Joshua V. Stough; Chuyang Ye; Sarah H. Ying; Jerry L. Prince (ISBI, 2013)

Automatic Method for Thalamus Parcellation Using Multi-modal Feature Classification. - Joshua V. Stough; Jeffrey Glaister; Chuyang Ye; Sarah H. Ying; Jerry L. Prince; Aaron Carass (MICCAI (3), 2014)

Thalamus parcellation using multi-modal feature classification and thalamic nuclei priors. - Jeffrey Glaister; Aaron Carass; Joshua V. Stough; Peter A. Calabresi; Jerry L. Prince (Image Processing, 2016)

Thalamus segmentation using multi-modal feature classification: Validation and pilot study of an age-matched cohort. - Jeffrey Glaister; Aaron Carass; Tziona NessAiver; Joshua V. Stough; Shiv Saidha; Peter A. Calabresi; Jerry L. Prince (NeuroImage, 2017)

Ventricular segmentation and quantitative assessment in cardiac MR using convolutional neural networks. - Joshua V. Stough; Joseph DiPalma; Zilin Ma; Brandon K. Fornwalt; Christopher M. Haggerty (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2018)

Interpretable Neural Networks for Predicting Mortality Risk using Multi-modal Electronic Health Records. - Alvaro E. Ulloa Cerna; Marios Pattichis; David P. vanMaanen; Linyuan Jing; Aalpen A. Patel; Joshua V. Stough; Christopher M. Haggerty; Brandon K. Fornwalt (CoRR, 2019)

Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data. - Sushravya Raghunath; Alvaro E. Ulloa Cerna; Linyuan Jing; David P. vanMaanen; Joshua Stough; Dustin N. Hartzel; Joseph B. Leader; H. Lester Kirchner; Christopher W. Good; Aalpen A. Patel; Brian P. Delisle; Amro Alsaid; et al. (CoRR, 2019)

Left ventricular and atrial segmentation of 2D echocardiography with convolutional neural networks. - Joshua V. Stough; Sushravya Raghunath; Xiaoyan Zhang; John M. Pfeifer; Brandon K. Fornwalt; Christopher M. Haggerty (Image Processing, 2020)

Bayesian Optimization of 2D Echocardiography Segmentation. - Tung Tran 005; Joshua V. Stough; Xiaoyan Zhang; Christopher M. Haggerty (ISBI, 2021)

Assessing the generalizability of temporally coherent echocardiography video segmentation. - Yida Chen; Xiaoyan Zhang; Christopher M. Haggerty; Joshua V. Stough (Image Processing, 2021)

Smartphone-Based Turbidity Estimation with Inherent Calibration. - Ding Zhang; Alan Marchiori; Joshua Stough (CSCI, 2022)

Fully automated multi-heartbeat echocardiography video segmentation and motion tracking. - Yida Chen; Xiaoyan Zhang; Christopher M. Haggerty; Joshua V. Stough (Image Processing, 2022)

Perceptually improved T1-T2 MRI translations using conditional generative adversarial networks. - Anurag Vaidya; Joshua V. Stough; Aalpen A. Patel (Image Processing, 2022)

Bayesian Optimization of 2D Echocardiography Segmentation. - Son-Tung Tran; Joshua V. Stough; Xiaoyan Zhang; Christopher M. Haggerty (CoRR, 2022)

Co-Unet-GAN: a co-learning domain adaptation model on echocardiography segmentation. - Junyang Cai; Christopher M. Haggerty; Joshua V. Stough (Image Processing, 2023)

A Large-scale Multimodal Study for Predicting Mortality Risk Using Minimal and Low Parameter Models and Separable Risk Assessment. - Alvaro E. Ulloa Cerna; David P. vanMaanen; Linyuan Jing; Joshua V. Stough; Aalpen A. Patel; Christopher M. Haggerty; Brandon K. Fornwalt; Marios S. Pattichis (IEEE J. Biomed. Health Informatics, 2025)