Autoencoder embedding of task-specific information. - Jason L. Granstedt; Weimin Zhou; Mark A. Anastasio (Image Perception, Observer Performance, and Technology Assessment, 2019)

Learning efficient channels with a dual loss autoencoder. - Jason L. Granstedt; Weimin Zhou; Mark A. Anastasio (Image Perception, Observer Performance, and Technology Assessment, 2020)

Approximating the Hotelling Observer with Autoencoder-Learned Efficient Channels for Binary Signal Detection Tasks. - Jason L. Granstedt; Weimin Zhou; Mark A. Anastasio (CoRR, 2020)

SlabGAN: a method for generating efficient 3D anisotropic medical volumes using generative adversarial networks. - Jason L. Granstedt; Varun A. Kelkar; Weimin Zhou; Mark A. Anastasio (Image Processing, 2021)

Task-based evaluation of deep image super-resolution in medical imaging. - Varun A. Kelkar; Xiaohui Zhang 012; Jason L. Granstedt; Hua Li 003; Mark A. Anastasio (Image Perception, Observer Performance, and Technology Assessment, 2021)

Advancing the AmbientGAN for learning stochastic object models. - Weimin Zhou; Sayantan Bhadra; Frank J. Brooks; Jason L. Granstedt; Hua Li 003; Mark A. Anastasio (Image Perception, Observer Performance, and Technology Assessment, 2021)

Impact of deep learning-based image super-resolution on binary signal detection. - Xiaohui Zhang 012; Varun A. Kelkar; Jason L. Granstedt; Hua Li 003; Mark A. Anastasio (CoRR, 2021)

Learned Hotelling observers for use with multi-modal data. - Jason L. Granstedt; Fu Li; Umberto Villa; Mark A. Anastasio (Image Perception, Observer Performance, and Technology Assessment, 2022)