A maximum-likelihood approach for ADC estimation of lesions in visceral organs. - Abhinav K. Jha; Jeffrey J. Rodriguez (SSIAI, 2012)

A radiative transfer equation-based image-reconstruction method incorporating boundary conditions for diffuse optical imaging. - Abhinav K. Jha; Yansong Zhu; Dean F. Wong; Arman Rahmim (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2017)

Use of Sub-Ensembles and Multi-Template Observers to Evaluate Detection Task Performance for Data That are Not Multivariate Normal. - Xin Li; Abhinav K. Jha; Michael Ghaly; Fatma E. A. Elshahaby; Jonathan M. Links; Eric C. Frey (IEEE Trans. Medical Imaging, 2017)

Incorporating CT prior information in the robust fuzzy C-means algorithm for QSPECT image segmentation. - Junyu Chen; Abhinav K. Jha; Eric C. Frey (Image Processing, 2019)

A List-Mode OSEM-Based Attenuation and Scatter Compensation Method for SPECT. - Md. Ashequr Rahman; Richard Laforest; Abhinav K. Jha (ISBI, 2020)

An estimation-based method to segment PET images. - Ziping Liu; Richard Laforest; Joyce C. Mhlanga; Hae Sol Moon; Tyler J. Fraum; Malak Itani; Aaron M. Mintz; Farrokh Dehdashti; Barry A. Siegel; Abhinav K. Jha (CoRR, 2020)

Observer study-based evaluation of a stochastic and physics-based method to generate oncological PET images. - Ziping Liu; Richard Laforest; Joyce C. Mhlanga; Tyler J. Fraum; Malak Itani; Farrokh Dehdashti; Barry A. Siegel; Abhinav K. Jha (Image Perception, Observer Performance, and Technology Assessment, 2021)

Task-based assessment of binned and list-mode SPECT systems. - Md. Ashequr Rahman; Abhinav K. Jha (Image Perception, Observer Performance, and Technology Assessment, 2021)

Ideal-Observer Computation with Anthropomorphic Phantoms using Markov Chain Monte Carlo. - Md. Ashequr Rahman; Zitong Yu; Abhinav K. Jha (ISBI, 2022)

No-gold-standard evaluation of quantitative imaging methods in the presence of correlated noise. - Ziping Liu; Zekun Li 012; Joyce C. Mhlanga; Barry A. Siegel; Abhinav K. Jha (Image Perception, Observer Performance, and Technology Assessment, 2022)

Investigating the limited performance of a deep-learning-based SPECT denoising approach: an observer-study-based characterization. - Zitong Yu; Md. Ashequr Rahman; Abhinav K. Jha (Image Perception, Observer Performance, and Technology Assessment, 2022)

Issues and Challenges in Applications of Artificial Intelligence to Nuclear Medicine - The Bethesda Report (AI Summit 2022). - Arman Rahmim; Tyler J. Bradshaw; Irène Buvat; Joyita Dutta; Abhinav K. Jha; Paul E. Kinahan; Quanzheng Li; Chi Liu; Melissa D. McCradden; Babak Saboury; Eliot L. Siegel; John J. Sunderland; et al. (CoRR, 2022)

Observer study-based evaluation of TGAN architecture used to generate oncological PET images. - Roberto Fedrigo; Fereshteh Yousefirizi; Ziping Liu; Abhinav K. Jha; Robert V. Bergen; Jean-François Rajotte; Raymond T. Ng; Ingrid Bloise; Sara Harsini; Dan J. Kadrmas; Carlos F. Uribe; Arman Rahmim (Image Perception, Observer Performance, and Technology Assessment, 2023)

Need for objective task-based evaluation of AI-based segmentation methods for quantitative PET. - Ziping Liu; Joyce C. Mhlanga; Barry A. Siegel; Abhinav K. Jha (Image Perception, Observer Performance, and Technology Assessment, 2023)

A task-specific deep-learning-based denoising approach for myocardial perfusion SPECT. - Md. Ashequr Rahman; Zitong Yu; Barry A. Siegel; Abhinav K. Jha (Image Perception, Observer Performance, and Technology Assessment, 2023)

Need for Objective Task-based Evaluation of Deep Learning-Based Denoising Methods: A Study in the Context of Myocardial Perfusion SPECT. - Zitong Yu; Md. Ashequr Rahman; Richard Laforest; Thomas H. Schindler; Robert J. Gropler; Richard L. Wahl; Barry A. Siegel; Abhinav K. Jha (CoRR, 2023)

A quality assurance framework for real-time monitoring of deep learning segmentation models in radiotherapy. - Xiyao Jin; Yao Hao; Jessica Hilliard; Zhehao Zhang; Maria A. Thomas; Hua Li; Abhinav K. Jha; Geoffrey D. Hugo (CoRR, 2023)

DEMIST: A deep-learning-based task-specific denoising approach for myocardial perfusion SPECT. - Md. Ashequr Rahman; Zitong Yu; Richard Laforest; Craig K. Abbey; Barry A. Siegel; Abhinav K. Jha (CoRR, 2023)

Nuclear Medicine Artificial Intelligence in Action: The Bethesda Report (AI Summit 2024). - Arman Rahmim; Tyler J. Bradshaw; Guido Davidzon; Joyita Dutta; Georges El Fakhri; Munir Ghesani; Nicolas A. Karakatsanis; Quanzheng Li; Chi Liu; Emilie Roncali; Babak Saboury; Tahir Yusufaly; et al. (CoRR, 2024)

Joint Regional Uptake Quantification of Thorium-227 and Radium-223 Using a Multiple-Energy-Window Projection-Domain Quantitative SPECT Method. - Zekun Li 012; Nadia Benabdallah; Richard Laforest; Richard L. Wahl; Daniel L. J. Thorek; Abhinav K. Jha (IEEE Trans. Medical Imaging, 2024)

CTLESS: A Scatter-Window Projection and Deep Learning-Based Transmission-Less Attenuation Compensation Method for Myocardial Perfusion SPECT. - Zitong Yu; Md. Ashequr Rahman; Craig K. Abbey; Richard Laforest; Nancy A. Obuchowski; Barry A. Siegel; Abhinav K. Jha (IEEE Trans. Medical Imaging, 2025)

A detection-task-specific deep-learning method to improve the quality of sparse-view myocardial perfusion SPECT images. - Zezhang Yang; Zitong Yu; Nuri Choi; Abhinav K. Jha (CoRR, 2025)

Emerging Frameworks for Objective Task-based Evaluation of Quantitative Medical Imaging Methods. - Yan Liu; Huitian Xia; Nancy A. Obuchowski; Richard Laforest; Arman Rahmim; Barry A. Siegel; Abhinav K. Jha (CoRR, 2025)