5 papers
Beyond Algorithms: Conceptual Innovation in Medical Imaging AI
Mark A. Anastasio
Artificial intelligence has driven rapid progress in medical imaging research, producing increasingly sophisticated algorithms and steady improvements on benchmark tasks. However,…
Input-Dependent Fisher Information for Local Sensitivity Analysis of Medical Image Classifiers
Sourya Sengupta. Mark A. Anastasio
Deep neural networks have achieved strong performance in medical image classification, but often work like black-box. Commonly used post-hoc interpretation methods often provide he…
Observer-Usable Information as a Task-specific Image Quality Metric
Changjie Lu, Sourya Sengupta, Hua Li +1
Objective, task-based measures of image quality (IQ) have been widely advocated for assessing and optimizing medical imaging technologies. Besides signal detection theory-based mea…
A Virtual Imaging Framework for Three-Dimensional Quantitative Optoacoustic Tomography Using Stochastic Numerical Breast Phantoms
Seonyeong Park, Gangwon Jeong, Umberto Villa +1
Optoacoustic tomography (OAT) is a promising modality for breast cancer diagnosis because tumor angiogenesis and, potentially, hypoxia can be visualized using quantitative OAT (qOA…
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…