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20222026
most citedDiffusion Models for Medical Image Analysis: A Comprehensive Survey

48 citations · 77 across the 18 of their papers we have counts for

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10 papers · 1 filter

eess.IV2026

XTinyU-Net: Training-Free U-Net Scaling via Initialization-Time Sensitivity

Alvin Kimbowa, Moein Heidari, David Liu +1

While U-Net architectures remain the gold standard for medical image segmentation, their deployment in resource-constrained environments demands aggressive model compression. Howev…

eess.IV2025

Echo-ENet: Efficient Endocardial Spatio-Temporal Network for Ejection Fraction Estimation

Moein Heidari, Afshin Bozorgpour, AmirHossein Zarif-Fakharnia +6

Left ventricular ejection fraction (LVEF) is a primary marker of cardiac function. However, routine estimation from endocardial measurements requires manual delineation at end-dias…

eess.IV2025

A Study on the Performance of U-Net Modifications in Retroperitoneal Tumor Segmentation

Moein Heidari, Ehsan Khodapanah Aghdam, Alexander Manzella +5

The retroperitoneum hosts a variety of tumors, including rare benign and malignant types, which pose diagnostic and treatment challenges due to their infrequency and proximity to v…

eess.IV2024★ 6 cited

MSANet: Multi-scale Adaptive Attention-guided Network for Medical Image Segmentation

Sina Ghorbani Kolahi, Seyed Kamal Chaharsooghi, Toktam Khatibi +5

Medical image segmentation involves identifying and separating object instances in a medical image to delineate various tissues and structures, a task complicated by the significan…

eess.IV2024★ 4 cited

Computation-Efficient Era: A Comprehensive Survey of State Space Models in Medical Image Analysis

Moein Heidari, Sina Ghorbani Kolahi, Sanaz Karimijafarbigloo +8

Sequence modeling plays a vital role across various domains, with recurrent neural networks being historically the predominant method of performing these tasks. However, the emerge…

eess.IV2024★ 2 cited

Enhancing Efficiency in Vision Transformer Networks: Design Techniques and Insights

Moein Heidari, Reza Azad, Sina Ghorbani Kolahi +8

Intrigued by the inherent ability of the human visual system to identify salient regions in complex scenes, attention mechanisms have been seamlessly integrated into various Comput…

eess.IV2024★ 1 cited

Vision-Language Synthetic Data Enhances Echocardiography Downstream Tasks

Pooria Ashrafian, Milad Yazdani, Moein Heidari +2

High-quality, large-scale data is essential for robust deep learning models in medical applications, particularly ultrasound image analysis. Diffusion models facilitate high-fideli…

eess.IV2022★ 48 cited

Diffusion Models for Medical Image Analysis: A Comprehensive Survey

Amirhossein Kazerouni, Ehsan Khodapanah Aghdam, Moein Heidari +4

Denoising diffusion models, a class of generative models, have garnered immense interest lately in various deep-learning problems. A diffusion probabilistic model defines a forward…

eess.IV2022

TransDeepLab: Convolution-Free Transformer-based DeepLab v3+ for Medical Image Segmentation

Reza Azad, Moein Heidari, Moein Shariatnia +4

Convolutional neural networks (CNNs) have been the de facto standard in a diverse set of computer vision tasks for many years. Especially, deep neural networks based on seminal arc…

eess.IV2022

Contextual Attention Network: Transformer Meets U-Net

Reza Azad, Moein Heidari, Yuli Wu +1

Currently, convolutional neural networks (CNN) (e.g., U-Net) have become the de facto standard and attained immense success in medical image segmentation. However, as a downside, C…