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 …

Myocardial function prediction after coronary artery bypass grafting using mri radiomic features and machine learning algorithms

F Arian, M Amini, S Mostafaei, K Rezaei Kalantari… - Journal of digital …, 2022 - Springer
The main aim of the present study was to predict myocardial function improvement in cardiac
MR (LGE-CMR) images in patients after coronary artery bypass grafting (CABG) using …

Dual-centre harmonised multimodal positron emission tomography/computed tomography image radiomic features and machine learning algorithms for non-small cell …

Z Khodabakhshi, M Amini, G Hajianfar, M Oveisi, I Shiri… - Clinical oncology, 2023 - Elsevier
Aims We aimed to build radiomic models for classifying non-small cell lung cancer (NSCLC)
histopathological subtypes through a dual-centre dataset and comprehensively evaluate the …

Interpretable PET/CT Radiomic Based Prognosis Modeling of NSCLC Recurrent Following Complete Resection

M Amini, S Mostafaei, M Poursamimi… - 2022 IEEE Nuclear …, 2022 - ieeexplore.ieee.org
This study aimed to develop an interpretable prognostic model with a nomogram for Non-
Small Cell Lung Cancer (NSCLC) recurrence prediction following complete resection, using …

PET and CT Information Fusion and Quality Assessment Toward Optimized Radiomic Features Extraction

M Amini, I Shiri, H Zaidi - 2022 IEEE Nuclear Science …, 2022 - ieeexplore.ieee.org
In this study, we performed two experiments to explore radiomic features and multi-modality
medical image fusion (IF). In the first experiment, we investigated the performance of …