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20212026
most citedMedical Image Segmentation Review: The success of U-Net

97 citations · 169 across the 20 of their papers we have counts for

collaborators

21 papers

cs.CV2026

HemaHier: Chain-Conditioned Ordinal Hierarchies for Lineage-Aware Bone-Marrow Cytology

Afshin Bozorgpour, Peter Schüffler, Edgar Jost +1

Bone-marrow cytology is inherently structured: each cell belongs to a hematopoietic lineage, and many cell types lie on ordered maturation trajectories. Standard flat classifiers i…

cs.CV2026

MaLViL: Multi-axis Low-rank Vision-LSTM for Medical Image Segmentation

Afshin Bozorgpour, Sina Ghorbani Kolahi, Moein Heidari +2

Vision-LSTM (ViL) enables efficient global modeling, but its cost still scales with the number of spatial tokens, so existing segmenters confine ViL to a coarse bottleneck and lose…

cs.CV2026

Gated Differential Linear Attention: A Linear-Time Decoder for High-Fidelity Medical Segmentation

Hongbo Zheng, Afshin Bozorgpour, Dorit Merhof +1

Medical image segmentation requires models that preserve fine anatomical boundaries while remaining practical for clinical deployment. Transformers capture long-range dependencies…

cs.CV2026

Footprint-Guided Exemplar-Free Continual Histopathology Report Generation

Pratibha Kumari, Daniel Reisenbüchler, Afshin Bozorgpour +3

Rapid progress in vision-language modeling has enabled pathology report generation from gigapixel whole-slide images, but most approaches assume static training with simultaneous a…

cs.CV2025

CENet: Context Enhancement Network for Medical Image Segmentation

Afshin Bozorgpour, Sina Ghorbani Kolahi, Reza Azad +2

Medical image segmentation, particularly in multi-domain scenarios, requires precise preservation of anatomical structures across diverse representations. While deep learning has a…

cs.CV2025

Attention-based Generative Latent Replay: A Continual Learning Approach for WSI Analysis

Pratibha Kumari, Daniel Reisenbüchler, Afshin Bozorgpour +3

Whole slide image (WSI) classification has emerged as a powerful tool in computational pathology, but remains constrained by domain shifts, e.g., due to different organs, diseases,…

cs.LG2025

Domain-incremental White Blood Cell Classification with Privacy-aware Continual Learning

Pratibha Kumari, Afshin Bozorgpour, Daniel Reisenbüchler +4

White blood cell (WBC) classification plays a vital role in hematology for diagnosing various medical conditions. However, it faces significant challenges due to domain shifts caus…

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…

cs.CV2024★ 2 cited

Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?

Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang +50

How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified…

eess.IV2024★ 1 cited

Physics-Inspired Generative Models in Medical Imaging: A Review

Dennis Hein, Afshin Bozorgpour, Dorit Merhof +1

Physics-inspired Generative Models (GMs), in particular Diffusion Models (DMs) and Poisson Flow Models (PFMs), enhance Bayesian methods and promise great utility in medical imaging…

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★ 1 cited

LHU-Net: a Lean Hybrid U-Net for Cost-efficient, High-performance Volumetric Segmentation

Yousef Sadegheih, Afshin Bozorgpour, Pratibha Kumari +2

The rise of Transformer architectures has advanced medical image segmentation, leading to hybrid models that combine Convolutional Neural Networks (CNNs) and Transformers. However,…

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.IV2023★ 2 cited

Continual Learning in Medical Image Analysis: A Comprehensive Review of Recent Advancements and Future Prospects

Pratibha Kumari, Joohi Chauhan, Afshin Bozorgpour +3

Medical imaging analysis has witnessed remarkable advancements even surpassing human-level performance in recent years, driven by the rapid development of advanced deep-learning al…

cs.CV2023★ 2 cited

HCA-Net: Hierarchical Context Attention Network for Intervertebral Disc Semantic Labeling

Afshin Bozorgpour, Bobby Azad, Reza Azad +3

Accurate and automated segmentation of intervertebral discs (IVDs) in medical images is crucial for assessing spine-related disorders, such as osteoporosis, vertebral fractures, or…

cs.CV2023★ 41 cited

Foundational Models in Medical Imaging: A Comprehensive Survey and Future Vision

Bobby Azad, Reza Azad, Sania Eskandari +4

Foundation models, large-scale, pre-trained deep-learning models adapted to a wide range of downstream tasks have gained significant interest lately in various deep-learning proble…

cs.CV2023

Unlocking Fine-Grained Details with Wavelet-based High-Frequency Enhancement in Transformers

Reza Azad, Amirhossein Kazerouni, Alaa Sulaiman +4

Medical image segmentation is a critical task that plays a vital role in diagnosis, treatment planning, and disease monitoring. Accurate segmentation of anatomical structures and a…

eess.IV2023★ 1 cited

DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation

Afshin Bozorgpour, Yousef Sadegheih, Amirhossein Kazerouni +2

Skin lesion segmentation plays a critical role in the early detection and accurate diagnosis of dermatological conditions. Denoising Diffusion Probabilistic Models (DDPMs) have rec…

eess.IV2022★ 97 cited

Medical Image Segmentation Review: The success of U-Net

Reza Azad, Ehsan Khodapanah Aghdam, Amelie Rauland +7

Automatic medical image segmentation is a crucial topic in the medical domain and successively a critical counterpart in the computer-aided diagnosis paradigm. U-Net is the most wi…

eess.IV2021★ 10 cited

Multi-scale Regional Attention Deeplab3+: Multiple Myeloma Plasma Cells Segmentation in Microscopic Images

Afshin Bozorgpour, Reza Azad, Eman Showkatian +1

Multiple myeloma cancer is a type of blood cancer that happens when the growth of abnormal plasma cells becomes out of control in the bone marrow. There are various ways to diagnos…