9 citations · 9 across the 2 of their papers we have counts for
Showing eess.IVShow all
3 papers · 1 filter
eess.IV2024★ 1 cited
Rethinking Perceptual Metrics for Medical Image Translation
Nicholas Konz, Yuwen Chen, Hanxue Gu +2
Modern medical image translation methods use generative models for tasks such as the conversion of CT images to MRI. Evaluating these methods typically relies on some chosen downst…
eess.IV2023
Reverse Engineering Breast MRIs: Predicting Acquisition Parameters Directly from Images
Nicholas Konz, Maciej A. Mazurowski
The image acquisition parameters (IAPs) used to create MRI scans are central to defining the appearance of the images. Deep learning models trained on data acquired using certain p…
eess.IV2022★ 9 cited
The Intrinsic Manifolds of Radiological Images and their Role in Deep Learning
Nicholas Konz, Hanxue Gu, Haoyu Dong +1
The manifold hypothesis is a core mechanism behind the success of deep learning, so understanding the intrinsic manifold structure of image data is central to studying how neural n…