1 citations · 2 across the 3 of their papers we have counts for
4 papers
Convolutional Neural Network Model Observers Discount Signal-like Anatomical Structures During Search in Virtual Digital Breast Tomosynthesis Phantoms
Aditya Jonnalagadda, Bruno B. Barufaldi, Andrew D. A. Maidment +3
Model observers are computational tools to evaluate and optimize task-based medical image quality. Linear model observers, such as the Channelized Hotelling Observer (CHO), predict…
Greater benefits of deep learning-based computer-aided detection systems for finding small signals in 3D volumetric medical images
Devi Klein, Srijita Karmakar, Aditya Jonnalagadda +2
Purpose: Radiologists are tasked with visually scrutinizing large amounts of data produced by 3D volumetric imaging modalities. Small signals can go unnoticed during the 3d search…
FoveaTer: Foveated Transformer for Image Classification
Aditya Jonnalagadda, William Yang Wang, B. S. Manjunath +1
Many animals and humans process the visual field with a varying spatial resolution (foveated vision) and use peripheral processing to make eye movements and point the fovea to acqu…
Towards Metamerism via Foveated Style Transfer
Arturo Deza, Aditya Jonnalagadda, Miguel Eckstein
The problem of is defined as finding a family of perceptually indistinguishable, yet physically different images. In this paper, we propose our NeuroFo…