13 citations · 30 across the 17 of their papers we have counts for
8 papers · 1 filter
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…
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-…
DAWN-FM: Data-Aware and Noise-Informed Flow Matching for Solving Inverse Problems
Shadab Ahamed, Eldad Haber
Inverse problems, which involve estimating parameters from incomplete or noisy observations, arise in various fields such as medical imaging, geophysics, and signal processing. The…
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…
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…
A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset
Shadab Ahamed, Yixi Xu, Ingrid Bloise +5
Automated slice classification is clinically relevant since it can be incorporated into medical image segmentation workflows as a preprocessing step that would flag slices with a h…
A cascaded deep network for automated tumor detection and segmentation in clinical PET imaging of diffuse large B-cell lymphoma
Shadab Ahamed, Natalia Dubljevic, Ingrid Bloise +6
Accurate detection and segmentation of diffuse large B-cell lymphoma (DLBCL) from PET images has important implications for estimation of total metabolic tumor volume, radiomics an…
Generalized Dice Focal Loss trained 3D Residual UNet for Automated Lesion Segmentation in Whole-Body FDG PET/CT Images
Shadab Ahamed, Arman Rahmim
Automated segmentation of cancerous lesions in PET/CT images is a vital initial task for quantitative analysis. However, it is often challenging to train deep learning-based segmen…