A method for measuring the accuracy of multi-modal image fusion system for catheter-based cardiac interventions using a novel motion enabled targeting phantom. - Charles R. Hatt; Douglas Stanton; Vijay Parthasarathy; Ameet K. Jain; Amish N. Raval (EMBC, 2011)

Real-Time 3D Ultrasound Guided Interventional System for Cardiac Stem Cell Therapy with Motion Compensation. - Vijay Parthasarathy; Charles R. Hatt; Zoran Stankovic; Amish Raval; Ameet K. Jain (MICCAI (1), 2011)

Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discrimination. - Won Hwa Kim; Deepti Pachauri; Charles R. Hatt; Moo K. Chung; Sterling C. Johnson; Vikas Singh (NIPS, 2012)

MRI - 3D ultrasound - X-ray image fusion with electromagnetic tracking for transendocardial therapeutic injections: In-vitro validation and in-vivo feasibility. - Charles R. Hatt; Ameet K. Jain; Vijay Parthasarathy; Andrew Lang; Amish Raval (Comput. Medical Imaging Graph., 2013)

Efficient feature-based 2D/3D registration of transesophageal echocardiography to x-ray fluoroscopy for cardiac interventions. - Charles R. Hatt; Michael A. Speidel; Amish N. Raval (Image-Guided Procedures, 2014)

Robust 5DOF Transesophageal Echo Probe Tracking at Fluoroscopic Frame Rates. - Charles R. Hatt; Michael A. Speidel; Amish N. Raval (MICCAI (1), 2015)

Hough Forests for Real-Time, Automatic Device Localization in Fluoroscopic Images: Application to TAVR. - Charles R. Hatt; Michael A. Speidel; Amish N. Raval (MICCAI (1), 2015)

Enhanced needle localization in ultrasound using beam steering and learning-based segmentation. - Charles R. Hatt; Gary Ng; Vijay Parthasarathy (Comput. Medical Imaging Graph., 2015)

Dynamic tracking of prosthetic valve motion and deformation from bi-plane x-ray views: feasibility study. - Charles R. Hatt; Martin G. Wagner; Amish N. Raval; Michael A. Speidel (Image-Guided Procedures, 2016)

Real-time pose estimation of devices from x-ray images: Application to x-ray/echo registration for cardiac interventions. - Charles R. Hatt; Michael A. Speidel; Amish N. Raval (Medical Image Anal., 2016)

Convolutional Neural Network Based COPD and Emphysema Classifications Are Predictive of Lung Cancer Diagnosis. - Charles R. Hatt; Craig J. Galbán; Wassim Labaki; Ella A. Kazerooni; David Lynch; Meilan Han (RAMBO+BIA+TIA@MICCAI, 2018)

A Convolutional Neural Network Approach to Automated Lung Bounding Box Estimation from Computed Tomography Scans. - Charles R. Hatt; Sundaresh Ram; Craig J. Galbán (DSW, 2019)

Lung Lobe Segmentation With Automated Quality Assurance Using Deep Convolutional Neural Networks. - Sundaresh Ram; Stephen M. Humphries; David A. Lynch; Craig J. Galbán; Charles R. Hatt (ISBI Workshops, 2020)

Segmentation of the thoracic aorta using an attention-gated U-Net. - Jiayang Zhong; Zhangxing Bian; Charles R. Hatt; Nicholas S. Burris (Computer-Aided Diagnosis, 2021)

A deformable image registration based method to assess directionality of thoracic aortic aneurysm growth. - Zhangxing Bian; Jiayang Zhong; Charles R. Hatt; Nicholas S. Burris (Image Processing, 2021)

Lung Cancer Lesion Detection in Histopathology Images Using Graph-Based Sparse PCA Network. - Sundaresh Ram; Wenfei Tang; Alexander J. Bell; Cara Spencer; Alexander Buschhaus; Charles R. Hatt; Marina Pasca diMagliano; Jeffrey J. Rodríguez; Stefanie Galban; Craig J. Galbán (CoRR, 2021)

LitCall: learning implicit topology for CNN-based aortic landmark localization. - Zhangxing Bian; Jiayang Zhong; Yanglong Lu; Chuck R. Hatt; Nicholas S. Burris (Image Processing, 2022)

Fully automated aortic measurements via CNN-based joint segmentation and localization. - Sudeep Katakol; Zhangxing Bian; Yanglong Lu; Greg Spahlinger; Charles R. Hatt; Nicholas S. Burris (Computer-Aided Diagnosis, 2023)

Deep Learning-Based Air Trapping Quantification Using Paired Inspiratory-Expiratory Ultra-low Dose CT. - Sarah M. Muller; Sundaresh Ram; Katie J. Bayfield; Julia H. Reuter; Sonja Gestewitz; Lifeng Yu; Mark Oliver Wielpütz; Hans-Ulrich Kauczor; Claus Peter Heussel; Terry E. Robinson; Brian J. Bartholmai; Charles R. Hatt; et al. (MICCAI (3), 2023)