3 papers
eess.IV2025
On the Utility of Virtual Staining for Downstream Applications as it relates to Task Network Capacity
Sourya Sengupta, Jianquan Xu, Phuong Nguyen +3
Virtual staining, or in-silico-labeling, has been proposed to computationally generate synthetic fluorescence images from label-free images by use of deep learning-based image-to-i…
eess.IV2025
Evaluation of Machine-generated Biomedical Images via A Tally-based Similarity Measure
Frank J. Brooks, Rucha Deshpande
Super-resolution, in-painting, whole-image generation, unpaired style-transfer, and network-constrained image reconstruction each include an aspect of machine-learned image synthes…
eess.IV2024
Report on the AAPM Grand Challenge on deep generative modeling for learning medical image statistics
Rucha Deshpande, Varun A. Kelkar, Dimitrios Gotsis +5
The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report. The goal of this challenge was…