104 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Tarbiat Modares UniversityIR4 papers
- Iran University of Medical SciencesIR3 papers
- Shahid Beheshti University of Medical SciencesIR3 papers
- Johns Hopkins UniversityUS2 papers
- Macquarie UniversityAU2 papers
- University of British ColumbiaCA2 papers
- Wayne State UniversityUS2 papers
- Amirkabir University of TechnologyIR1 paper
- Brunel University of LondonGB1 paper
- Cedars-Sinai Medical CenterUS1 paper
- Child Health and Development InstituteUS1 paper
- École Nationale d'Ingénieurs de MetzFR1 paper
18 papers
Cataract-LMM Large-Scale Multi-Source Multi-Task Benchmark for Deep Learning in Surgical Video Analysis
Mohammad Javad Ahmadi, Iman Gandomi, Parisa Abdi +6
Computer-assisted surgery research requires large, deeply annotated video datasets that capture clinical and technical variability. Existing cataract surgery resources lack the div…
FoundBioNet: A Foundation-Based Model for IDH Genotyping of Glioma from Multi-Parametric MRI
Somayeh Farahani, Marjaneh Hejazi, Antonio Di Ieva +1
Accurate, noninvasive detection of isocitrate dehydrogenase (IDH) mutation is essential for effective glioma management. Traditional methods rely on invasive tissue sampling, which…
ExKG-LLM: Leveraging Large Language Models for Automated Expansion of Cognitive Neuroscience Knowledge Graphs
Ali Sarabadani, Kheirolah Rahsepar Fard, Hamid Dalvand
The paper introduces ExKG-LLM, a framework designed to automate the expansion of cognitive neuroscience knowledge graphs (CNKG) using large language models (LLMs). It addresses lim…
Diagnostic performance of deep learning for predicting glioma isocitrate dehydrogenase and 1p/19q co-deletion in MRI: a systematic review and meta-analysis
Somayeh Farahani, Marjaneh Hejazi, Mehnaz Tabassum +3
Objectives We aimed to evaluate the diagnostic performance of deep learning (DL)-based radiomics models for the noninvasive prediction of isocitrate dehydrogenase (IDH) mutation an…
Large Language Models versus Classical Machine Learning: Performance in COVID-19 Mortality Prediction Using High-Dimensional Tabular Data
Mohammadreza Ghaffarzadeh-Esfahani, Mahdi Ghaffarzadeh-Esfahani, Arian Salahi-Niri +39
This study compared the performance of classical feature-based machine learning models (CMLs) and large language models (LLMs) in predicting COVID-19 mortality using high-dimension…
Comparison of the x-ray tube spectrum measurement using BGO, NaI, LYSO, and HPGe detectors in a preclinical mini-CT scanner: Monte Carlo simulation and practical experiment
Vahid Lohrabian, Alireza Kamali-Asl, Hossein Ghadiri Harvani +2
The aim of this study is to estimate the intrinsic efficiency and energy resolution of different types of solid-state gamma-ray detectors in order to generate a precise dual-energy…
Accurate and Rapid Diagnosis of COVID-19 Pneumonia with Batch Effect Removal of Chest CT-Scans and Interpretable Artificial Intelligence
Rassa Ghavami Modegh, Mehrab Hamidi, Saeed Masoudian +22
COVID-19 is a virus with high transmission rate that demands rapid identification of the infected patients to reduce the spread of the disease. The current gold-standard test, Reve…
Medical Imaging and Computational Image Analysis in COVID-19 Diagnosis: A Review
Shahabedin Nabavi, Azar Ejmalian, Mohsen Ebrahimi Moghaddam +4
Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. The disease presents with symptoms such as shortness of breath, fever, dry cough,…
Sleep Stage Scoring Using Joint Frequency-Temporal and Unsupervised Features
Mohamadreza Jafaryani, Saeed Khorram, Vahid Pourahmadi +1
Patients with sleep disorders can better manage their lifestyle if they know about their special situations. Detection of such sleep disorders is usually possible by analyzing a nu…
Quantifying Cortical Bone Free Water Using short echo time (STE-MRI) at 1.5T
Shahrokh Abbasi-Rad, Atena Akbari, Malakeh Malekzadeh +3
Purpose: The purpose of our study was to use Dual-TR STE-MR protocol as a clinical tool for cortical bone free water quantification at 1.5T and validate it by comparing the obtaine…
Concentration of Benefit index: A threshold-free summary metric for quantifying the capacity of covariates to yield efficient treatment rules
Mohsen Sadatsafavi, Mohammad Ali Mansournia, Paul Gustafson
When data on treatment assignment, outcomes, and covariates from a randomized trial are available, a question of interest is to what extent covariates can be used to optimize treat…
Continuous and Pulsed Experiments with Numerical Simulation to Dissect Pituitary Gland Tumour by Using Liquid Jet
Ahmed H. Alamoud, Emmanuel Baillot, Camila Belabbas +4
Endoscopic endonasal surgery is a minimal invasive surgery that has been used to dissect pituitary gland tumour via curettes with the help of endoscope. However, this type of surge…
A threshold-free summary index for quantifying the capacity of covariates to yield efficient treatment rules
Mohsen Sadatsafavi, Mohammad Mansournia, Paul Gustafson
The focus of this paper is on quantifying the capacity of covariates in devising efficient treatment rules when data from a randomized trial are available. Conventional one-variabl…
An Efficient Nonlinear Beamformer Based on P^{th} Root of Detected Signals for Linear-Array Photoacoustic Tomography: Application to Sentinel Lymph Node Imaging
Moein Mozaffarzadeh, Vijitha Periyasamy, Manojit Pramanik +1
In linear-array transducer based photoacoustic (PA) imaging, B-scan PA images are formed using the raw channel PA signals. Delay-and-Sum (DAS) is the most prevalent algorithm due t…
An Analysis Scheme for Investigation of Effects of Various Parameters on Signals in Acoustic-Resolution Photoacoustic Microscopy of Mice Brain: a Simulation Study
Hossein Ghadiri, Mohammad Reza Fouladi, Arman Rahmim
Photoacoustic spectral analysis is a novel tool for studying various parameters affecting signals in Photoacoustic microscopy. But only observing frequency components of photoacous…
An Image Registration Based Technique for Noninvasive Vascular Elastography
Sina Valizadeh, Bahador Makkiabadi, Alireza Mirbagheri +4
Non-invasive vascular elastography is an emerging technique in vascular tissue imaging. During the past decades, several techniques have been suggested to estimate the tissue elast…
Enhanced Linear-array Photoacoustic Beamforming using Modified Coherence Factor
Moein Mozaffarzadeh, Yan Yan, Mohammad Mehrmohammadi +1
Photoacoustic imaging (PAI) is a promising medical imaging modality providing the spatial resolution of ultrasound (US) imaging and the contrast of pure optical imaging. For linear…
Design of Fuzzy self-tuning PID controller for pitch control system of aircraft autopilot
Nima Beygi, Maani Beigy, Mehdi Siahi
A variety of control systems have been proposed for aircraft autopilot systems. Traditional approaches such as proportional controller and conventional PID (CPID) controller are wi…