A5089860742- Medical Imaging Techniques and Applications
- Advanced X-ray and CT Imaging
- Cardiac Imaging and Diagnostics
- Radiomics and Machine Learning in Medical Imaging
- Advanced MRI Techniques and Applications
- Radiopharmaceutical Chemistry and Applications
- Cardiovascular Function and Risk Factors
- Radiation Dose and Imaging
- Dendrimers and Hyperbranched Polymers
- Advanced Radiotherapy Techniques
- Radiology practices and education
- Monoclonal and Polyclonal Antibodies Research
- Colorectal Cancer Surgical Treatments
- Radiation Therapy and Dosimetry
- Digital Radiography and Breast Imaging
- Nanocluster Synthesis and Applications
- Lung Cancer Treatments and Mutations
- Thyroid Cancer Diagnosis and Treatment
- Cardiovascular Disease and Adiposity
- Atomic and Subatomic Physics Research
- Cardiac electrophysiology and arrhythmias
- Cardiac Structural Anomalies and Repair
- Medical Imaging and Pathology Studies
- Cardiac Valve Diseases and Treatments
- Nanoparticle-Based Drug Delivery
Iran University of Medical Sciences
2016-2025
Shaheed Rajaei Cardiovascular Medical and Research Center
2016-2025
Tehran University of Medical Sciences
2012-2022
University of Toronto
2022
Tarbiat Modares University
2003-2009
Abbasi Shaheed Hospital
2009
University of Guilan
2009
Robust differentiation between infarcted and normal tissue is important for clinical diagnosis precision medicine. The aim of this work to investigate the radiomic features develop a machine learning algorithm myocardial infarction (MI) viable tissues/normal cases in left ventricular myocardium on non-contrast Cine Cardiac Magnetic Resonance (Cine-CMR) images.Seventy-two patients (52 with MI 20 healthy control patients) were enrolled study. MR imaging was performed 1.5 T MRI using following...
The targeted delivery of superparamagnetic iron oxide nanoparticles (SPIONs) as a contrast agent may facilitate their accumulation in cancer cells and enhance the sensitivity MR imaging. In this study, SPIONs coated with dextran (DSPIONs) were conjugated bombesin (BBN) to produce targeting for detection breast using MRI. X-ray diffraction, transmission electron microscopy, vibrating sample magnetometer analyses indicated formation dextran-coated an average size 6.0 ± 0.5 nm. Fourier...
Abstract A U-shaped contraction pattern was shown to be associated with a better Cardiac resynchronization therapy (CRT) response. The main goal of this study is automatically recognize left ventricular contractile patterns using machine learning algorithms trained on conventional quantitative features (ConQuaFea) and radiomic extracted from Gated single-photon emission computed tomography myocardial perfusion imaging (GSPECT MPI). Among 98 patients standard resting GSPECT MPI included in...
This study intends to predict in-hospital and 6-month mortality, as well 30-day 90-day hospital readmission, using Machine Learning (ML) approach via conventional features. A total of 737 patients remained after applying the exclusion criteria 1101 heart failure patients. Thirty-four features were collected for each patient. First, data divided into train test cohorts with a 70-30% ratio. Then normalized Z-score method, its mean standard deviation applied data. Subsequently, Boruta, RFE,...
Molecular theranostics is of the utmost interest for diagnosis as well treatment different malignancies. In present study, anionic linear globular dendrimer G2 employed a suitable carrier delivery and AS1411 aptamer exploited targeting agent to carry Iohexol specifically human breast cancer cells (MCF-7). Dendrimer was prepared conjugation carried out thereafter. Based on data yielded by AFM, morphology smooth spherical non-targeted changed rough aspherical shape when it conjugated. Then,...
While cancer is the leading cause of human's deaths worldwide, finding an imaging agent which can detect tumours needed for diagnosis. In present study, PEG-citrate dendrimer-G
The main aim of the present study was to predict myocardial function improvement in cardiac MR (LGE-CMR) images patients after coronary artery bypass grafting (CABG) using radiomics and machine learning algorithms. Altogether, 43 who had visible scars on short-axis LGE-CMR were candidates for CABG surgery selected enrolled this study. imaging performed preoperatively a 1.5-T MRI scanner. All segmented by two expert radiologists (in consensus). Prior extraction features, all resampled an...
Whole-body bone scintigraphy (WBS) is one of the most widely used modalities in diagnosing malignant diseases during early stages. However, procedure time-consuming and requires vigour experience. Moreover, interpretation WBS scans stages disorders might be challenging because patterns often reflect normal appearance that prone to subjective interpretation. To simplify gruelling, subjective, prone-to-error task interpreting scans, we developed deep learning (DL) models automate two major...
Abstract Introduction Providing tools for comprehensively evaluating scintigraphy images could enhance transthyretin amyloid cardiomyopathy (ATTR-CM) diagnosis. This study aims to automatically detect and score ATTR-CM in total body using deep learning on multi-tracer, multi-scanner, multi-center datasets. Methods In the current study, we employed six datasets (from 12 cameras) various tasks purposes. Dataset #1 (93 patients, 99m Tc-MDP) was used develop 2D-planar segmentation localization...
Abstract Background Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is a well-established modality for noninvasive diagnostic assessment of coronary artery disease (CAD). However, the time-consuming and experience-dependent visual interpretation SPECT images remains limitation in clinic. Purpose We aimed to develop advanced models diagnose CAD different supervised semi-supervised deep learning (DL) algorithms training strategies, including transfer...
Early detection of malignant thyroid nodules is crucial for effective treatment, but traditional diagnostic methods face challenges such as variability in expert opinions and limited integration advanced imaging techniques. This prospective cohort study investigates a novel multimodal approach, integrating with machine learning We studied 181 patients who underwent fine-needle aspiration (FNA) biopsy, each contributing one nodule, resulting total our analysis. Data collection included sex,...
In this study, the ability of radiomics features extracted from myocardial perfusion imaging with SPECT (MPI-SPECT) was investigated for prediction ejection fraction (EF) post-percutaneous coronary intervention (PCI) treatment. A total 52 patients who had undergone pre-PCI MPI-SPECT were enrolled in study. After normalization images, left ventricle, initially automatically segmented by k-means and active contour methods, finally edited approved an expert radiologist. More than 1700 2D 3D...
It is more than 100 years since the first usage of X-ray.In early days its implementation, there was no vision about potential harms, 1,2 including various dermatoses, cataract, hematological disorders, and cancer, 3 which necessitates considering radiation protection (RP) strategies such as 'as low reasonably achievable' (ALARA) principle. 4For all medical imaging procedures, are three basic principles: justification, optimization, dose limits. 57][8] RP has been one main concerns...
Nowadays, molecular imaging radiopharmaceuticals', nanoparticles', and/or small-molecule biomarkers' applications are increasing rapidly worldwide. Thus, researchers focus on providing the novel, safe, and cost-effective ones.In present experiment, technetium-99m (99mTc)-labeled PEG-citrate dendrimer-G2 conjugated with glutamine (nanoconjugate) was designed assessed as a novel tumor probe both in vitro vivo. Nanoconjugate synthesized synthesis confirmed by Fourier transform infrared, proton...
Speckle noise is the main factor that degrades ultrasound image contrast and segmentation failure. Determining an effective filter can reduce speckle improve performances. The aim of this study was to define a useful outcome.Twelve filters, including median, hybrid median (Hmed), Fourier Butterworth, ideal, wavelet (Wlet), homomorphic (Hmp_Wlet), frost, anisotropic diffusion, probabilistic patch-based (PPB), homogeneous area were used find best filter(s) prepare thyroid nodule segmentation....
Abstract Heart failure caused by iron deposits in the myocardium is primary cause of mortality beta-thalassemia major patients. Cardiac magnetic resonance imaging (CMRI) T2* screening technique used to detect myocardial overload, but inherently bears some limitations. In this study, we aimed differentiate patients with overload from those without (detected T2*CMRI) based on radiomic features extracted echocardiography images and machine learning (ML) normal left ventricular ejection fraction...
Abstract Introduction Neoadjuvant chemoradiotherapy (nCRT) followed by surgical resection is the standard treatment for locally advanced rectal cancer (LARC). Radiomics can be used as noninvasive biomarker prediction of response to therapy. The main aim this study was evaluate association MRI texture features LARC with nCRT and effect Laplacian Gaussian (LoG) filter feature selection algorithm in process improvement. Methods All patients underwent a 3T clinical scanner, 1 week before nCRT....