8 citations · 21 across the 9 of their papers we have counts for
6 papers · 1 filter
How to Segment in 3D Using 2D Models: Automated 3D Segmentation of Prostate Cancer Metastatic Lesions on PET Volumes Using Multi-angle Maximum Intensity Projections and Diffusion Models
Amirhosein Toosi, Sara Harsini, François Bénard +2
Prostate specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) imaging provides a tremendously exciting frontier in visualization of prostate c…
Novel Method to Estimate Kinetic Microparameters from Dynamic Whole-Body Imaging in Regular-Axial Field-of-View PET Scanners
Kyung-Nam Lee, Arman Rahmim, Carlos Uribe
For whole-body (WB) kinetic modeling based on a typical PET scanner, a multi-pass multi-bed scanning protocol is necessary given the limited axial field-of-view. Such a protocol in…
RT-utils: A Minimal Python Library for RT-struct Manipulation
Asim Shrestha, Adam Watkins, Fereshteh Yousefirizi +2
Towards the need for automated and precise AI-based analysis of medical images, we present RT-utils, a specialized Python library tuned for the manipulation of radiotherapy (RT) st…
Investigating heterogeneous PSMA ligand uptake inside parotid glands
Caleb Sample, Carlos Uribe, Arman Rahmim +3
The purpose was to investigate the spatial heterogeneity of prostate-specific membrane antigen (PSMA) positron emission tomography (PET) uptake within parotid glands. We aim to qua…
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:…