State-of-the-art object detection algorithms for small lesion detection in PSMA PET: use of rotational maximum intensity projection (MIP) images. - Amirhosein Toosi; Sara Harsini; Shadab Ahamed; Fereshteh Yousefirizi; François Bénard; Carlos F. Uribe; Arman Rahmim (Image Processing, 2023)

Observer study-based evaluation of TGAN architecture used to generate oncological PET images. - Roberto Fedrigo; Fereshteh Yousefirizi; Ziping Liu; Abhinav K. Jha; Robert V. Bergen; Jean-François Rajotte; Raymond T. Ng; Ingrid Bloise; Sara Harsini; Dan J. Kadrmas; Carlos F. Uribe; Arman Rahmim (Image Perception, Observer Performance, and Technology Assessment, 2023)

Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss. - Yixi Xu; Ivan S. Klyuzhin; Sara Harsini; Anthony Ortiz; Shun Zhang; François Bénard; Rahul Dodhia; Carlos F. Uribe; Arman Rahmim; Juan Lavista Ferres (Comput. Biol. Medicine, 2023)

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; Carlos F. Uribe; Arman Rahmim (DGM4MICCAI@MICCAI, 2024)

Comprehensive Evaluation of Quantitative Measurements from Automated Deep Segmentations of PSMA PET/CT Images. - Obed Korshie Dzikunu; Amirhossein Toosi; Shadab Ahamed; Sara Harsini; François Bénard; Xiaoxiao Li; Arman Rahmim (CoRR, 2025)