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Journal of the Optical Society of America. A, Optics, Image Science, and Vision|February 19, 2005
Spherical-wave intensity diffraction tomographyGreg Gbur, Mark A Anastasio, Yin Huang, et al.Journal of Medical Imaging (Bellingham, Wash.)|March 24, 2025
Semi-supervised semantic segmentation of cell nuclei with diffusion model and collaborative learningZhuchen Shao, Sourya Sengupta, Mark A Anastasio, et al.IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control|September 8, 2023
A Forward Model Incorporating Elevation-Focused Transducer Properties for 3-D Full-Waveform Inversion in Ultrasound Computed TomographyFu Li, Umberto Villa, Nebojsa Duric, et al.Arxiv|January 30, 2023
A forward model incorporating elevation-focused transducer properties for 3D full-waveform inversion in ultrasound computed tomographyFu Li, Umberto Villa, Nebojsa Duric, et al.Photoacoustics|July 30, 2026
A virtual imaging framework for three-dimensional quantitative optoacoustic tomography using stochastic numerical breast phantomsSeonyeong Park, Gangwon Jeong, Umberto Villa, et al.Optics Letters|March 21, 2006
Image reconstruction in optoacoustic tomography for dispersive acoustic mediaPatrick J La Rivière, Jin Zhang, Mark A AnastasioIEEE Transactions on Medical Imaging|April 30, 2021
Assessing the Impact of Deep Neural Network-Based Image Denoising on Binary Signal Detection TasksKaiyan Li, Weimin Zhou, Hua Li, et al.Journal of Medical Imaging (Bellingham, Wash.)|October 23, 2025
Approximating the ideal observer for joint signal detection and estimation tasks by the use of Markov-Chain Monte Carlo with generative adversarial networksDan Li, Kaiyan Li, Weimin Zhou, et al.IEEE Transactions on Medical Imaging|December 13, 2021
A Hybrid Approach for Approximating the Ideal Observer for Joint Signal Detection and Estimation Tasks by Use of Supervised Learning and Markov-Chain Monte Carlo MethodsKaiyan Li, Weimin Zhou, Hua Li, et al.Physics in Medicine and Biology|July 27, 2004
Half-scan and single-plane intensity diffraction tomography for phase objectsDaxin Shi, Mark A Anastasio, Yin Huang, et al.Pageof 40