A review of PET attenuation correction methods for PET-MR

G Krokos, J MacKewn, J Dunn, P Marsden - EJNMMI physics, 2023 - Springer
Despite being thirteen years since the installation of the first PET-MR system, the scanners
constitute a very small proportion of the total hybrid PET systems installed. This is in stark …

Improving Pancreatic Cyst Management: Artificial Intelligence-Powered Prediction of Advanced Neoplasms through Endoscopic Ultrasound-Guided Confocal …

J Jiang, WL Chao, T Cao, S Culp, B Napoléon… - Biomimetics, 2023 - mdpi.com
Despite the increasing rate of detection of incidental pancreatic cystic lesions (PCLs),
current standard-of-care methods for their diagnosis and risk stratification remain …

Machine learning-based diagnosis and risk classification of coronary artery disease using myocardial perfusion imaging SPECT: A radiomics study

M Amini, M Pursamimi, G Hajianfar, Y Salimi… - Scientific reports, 2023 - nature.com
This study aimed to investigate the diagnostic performance of machine learning-based
radiomics analysis to diagnose coronary artery disease status and risk from rest/stress …

[HTML][HTML] Multi-institutional PET/CT image segmentation using federated deep transformer learning

I Shiri, B Razeghi, AV Sadr, M Amini, Y Salimi… - Computer Methods and …, 2023 - Elsevier
Abstract Background and Objective Generalizable and trustworthy deep learning models for
PET/CT image segmentation necessitates large diverse multi-institutional datasets …

Differential privacy preserved federated transfer learning for multi-institutional 68Ga-PET image artefact detection and disentanglement

I Shiri, Y Salimi, M Maghsudi, E Jenabi… - European journal of …, 2023 - Springer
Purpose Image artefacts continue to pose challenges in clinical molecular imaging, resulting
in misdiagnoses, additional radiation doses to patients and financial costs. Mismatch and …

PRIMIS: Privacy-preserving medical image sharing via deep sparsifying transform learning with obfuscation

I Shiri, B Razeghi, S Ferdowsi, Y Salimi… - Journal of biomedical …, 2024 - Elsevier
Objective: The primary objective of our study is to address the challenge of confidentially
sharing medical images across different centers. This is often a critical necessity in both …

Information fusion for fully automated segmentation of head and neck tumors from PET and CT images

I Shiri, M Amini, F Yousefirizi, A Vafaei Sadr… - Medical …, 2024 - Wiley Online Library
Background PET/CT images combining anatomic and metabolic data provide
complementary information that can improve clinical task performance. PET image …

Federated machine learning for predicting acute kidney injury in critically ill patients: a multicenter study in Taiwan

CT Huang, TJ Wang, LK Kuo, MJ Tsai, CT Cia… - … Information Science and …, 2023 - Springer
Purpose To address the contentious data sharing across hospitals, this study adopted a
novel approach, federated learning (FL), to establish an aggregate model for acute kidney …

The quest for multifunctional and dedicated PET instrumentation with irregular geometries

A Sanaat, M Amini, H Arabi, H Zaidi - Annals of Nuclear Medicine, 2024 - Springer
We focus on reviewing state-of-the-art developments of dedicated PET scanners with
irregular geometries and the potential of different aspects of multifunctional PET imaging …

[HTML][HTML] Artificial intelligence-based analysis of whole-body bone scintigraphy: The quest for the optimal deep learning algorithm and comparison with human …

G Hajianfar, M Sabouri, Y Salimi, M Amini… - … für Medizinische Physik, 2024 - Elsevier
Purpose Whole-body bone scintigraphy (WBS) is one of the most widely used modalities in
diagnosing malignant bone diseases during the early stages. However, the procedure is …