8 citations · 21 across the 9 of their papers we have counts for
3 papers · 1 filter
Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: clinical insights, pitfalls, and observer agreement analyses
Shadab Ahamed, Yixi Xu, Sara Kurkowska +12
This study addresses critical gaps in automated lymphoma segmentation from PET/CT images, focusing on issues often overlooked in existing literature. While deep learning has been a…
PyTomography: A Python Library for Medical Image Reconstruction
Lucas A. Polson, Roberto Fedrigo, Chenguang Li +8
There is a need for open-source libraries in emission tomography that (i) use modern and popular backend code to encourage community contributions and (ii) offer support for the mu…
Neural blind deconvolution for deblurring and supersampling PSMA PET
Caleb Sample, Arman Rahmim, Carlos Uribe +4
Objective: To simultaneously deblur and supersample prostate specific membrane antigen (PSMA) positron emission tomography (PET) images using neural blind deconvolution. Approach:…