From the 1 of 56 linked papers with an AI index.
2 citations · 2 across the 20 of their papers we have counts for
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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-…
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…
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…
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…
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…