24 citations · 48 across the 4 of their papers we have counts for
Showing eess.IVShow all
2 papers · 1 filter
eess.IV2025
Maintaining SUV Accuracy in Low-Count PET with PETfectior: A Deep Learning Denoising Solution
Yamila Rotstein Habarnau, Nicolás Bustos, Paola Corona +8
Background: Diagnostic PET image quality depends on the administered activity and acquisition time. However, minimizing these variables is desirable to reduce patient radiation exp…
eess.IV2023
A mirror-Unet architecture for PET/CT lesion segmentation
Yamila Rotstein Habarnau, Mauro Namías
Automatic lesion detection and segmentation from [F]FDG PET/CT scans is a challenging task, due to the diversity of shapes, sizes, FDG uptake and location they may present…