Mostafa Fatemi

Professor of Biomedical Engineering

Mayo Clinic College of Medicine and Science

United States

Research Interests

Explore related searches

Professors in United States Professors in Medical Imaging Medical Imaging professors in United States

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Mostafa Fatemi is a Professor of Biomedical Engineering at Mayo Clinic College of Medicine and Science in the United States. His research areas focus on advanced imaging techniques and artificial intelligence applications in healthcare, including fetal brain imaging, ultrasound microvessel imaging, and automated breast lesion segmentation. Recent publications highlight his work on quantitative biomarkers, deep learning methodologies, and the economics of AI in medical diagnostics.

Articles (15)

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Collaborators (6)

Athanase Protogerou

Professor

National and Kapodistrian University of Athens

GREECE

View details

Ferenc Nagy

Associate Professor

University of Szeged

HUNGARY

View details

Zoltán Ruzsa

HUNGARY

View details

Sophie Mavrogeni

Visiting Professor of Cardiovascular Imaging

National and Kapodistrian University of Athens

GREECE

View details

DESINENI NAIDU

University of Minnesota Duluth

UNITED STATES

View details

Gavino Faa

University of Cagliari

ITALY

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Mostafa Fatemi

Research Interests

Explore related searches

Contact this professor

About

Articles (15)

Artificial intelligence in fetal brain imaging: Advancements, challenges, and multimodal approaches for biometric and structural analysis

Quantitative Biomarkers Derived from a Novel, Contrast-Free Ultrasound, High-Definition Microvessel Imaging for Differentiating Choroidal Tumors

Background Noise Removal in Non-Contrast- Enhanced Ultrasound Microvasculature Imaging Using Combined Collaborative, Morphological, and Vesselness Filtering

DMAeEDNet: Dense Multiplicative Attention Enhanced Encoder Decoder Network for Ultrasound-Based Automated Breast Lesion Segmentation

Pulsed Vibro-Acoustic Analysis Technique for Monitoring Bone Health in Preterm Infants: A Pilot Study

Mapping Pharmacologically Evoked Neurovascular Activation and Its Suppression in a Rat Model of Tremor Using Functional Ultrasound: A Feasibility Study

Deep Learning in Different Ultrasound Methods for Breast Cancer, from Diagnosis to Prognosis: Current Trends, Challenges, and an Analysis

Quantitative Biomarkers Derived from a Novel Contrast-Free Ultrasound High-Definition Microvessel Imaging for Distinguishing Thyroid Nodules

Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment

Cardiovascular/Stroke Risk Stratification in Diabetic Foot Infection Patients Using Deep Learning-Based Artificial Intelligence: An Investigative Study

Experimental Study of Aperiodic Plane Wave Imaging for Ultrafast 3-D Ultrasound Imaging

Vascular Implications of COVID-19: Role of Radiological Imaging, Artificial Intelligence, and Tissue Characterization: A Special Report

COVLIAS 2.0-cXAI: Cloud-Based Explainable Deep Learning System for COVID-19 Lesion Localization in Computed Tomography Scans

Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinson’s Disease Affected by COVID-19: A Narrative Review

COVLIAS 1.0<sub>Lesion</sub> vs. MedSeg: An Artificial Intelligence Framework for Automated Lesion Segmentation in COVID-19 Lung Computed Tomography Scans

Collaborators (6)

Athanase Protogerou

Ferenc Nagy

Zoltán Ruzsa

Sophie Mavrogeni

DESINENI NAIDU

Gavino Faa

Make your next move.