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From the 1 of 56 linked papers with an AI index.

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20242026
most citedMathematical and Computational Nuclear Oncology: Toward Optimized Radiopharmaceutical Therapy via Digital Twins

2 citations · 2 across the 20 of their papers we have counts for

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eess.IV2026

Adaptive Voxel-Weighted Loss Using L1 Norms in Deep Neural Networks for Detection and Segmentation of Prostate Cancer Lesions in PET/CT Images

Obed Korshie Dzikunu, Shadab Ahamed, Amirhossein Toosi +2

Accurate automated detection of recurrent prostate cancer in PSMA PET/CT scans is challenging due to heterogeneous lesion size, activity, anatomical location, and intra- and inter-…

eess.IV2025

IgCONDA-PET: Weakly-Supervised PET Anomaly Detection using Implicitly-Guided Attention-Conditional Counterfactual Diffusion Modeling -- a Multi-Center, Multi-Cancer, and Multi-Tracer Study

Shadab Ahamed, Arman Rahmim

Minimizing the need for pixel-level annotated data to train PET lesion detection and segmentation networks is highly desired and can be transformative, given time and cost constrai…

eess.IV2025

Comprehensive Evaluation of Quantitative Measurements from Automated Deep Segmentations of PSMA PET/CT Images

Obed Korshie Dzikunu, Amirhossein Toosi, Shadab Ahamed +4

This study performs a comprehensive evaluation of quantitative measurements as extracted from automated deep-learning-based segmentation methods, beyond traditional Dice Similarity…

eess.IV2025

Application of Spherical Convolutional Neural Networks to Image Reconstruction and Denoising in Nuclear Medicine

Amirreza Hashemi, Yuemeng Feng, Arman Rahmim +1

This work investigates use of equivariant neural networks as efficient and high-performance frameworks for image reconstruction and denoising in nuclear medicine. Our work aims to…

eess.IV2024

Thyroidiomics: An Automated Pipeline for Segmentation and Classification of Thyroid Pathologies from Scintigraphy Images

Maziar Sabouri, Shadab Ahamed, Azin Asadzadeh +13

The objective of this study was to develop an automated pipeline that enhances thyroid disease classification using thyroid scintigraphy images, aiming to decrease assessment time…