97 citations · 489 across the 41 of their papers we have counts for
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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…
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…
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,…
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…
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…
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…
Implicit Neural Representation in Medical Imaging: A Comparative Survey
Amirali Molaei, Amirhossein Aminimehr, Armin Tavakoli +4
Implicit neural representations (INRs) have gained prominence as a powerful paradigm in scene reconstruction and computer graphics, demonstrating remarkable results. By utilizing n…
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…
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…
Attention Swin U-Net: Cross-Contextual Attention Mechanism for Skin Lesion Segmentation
Ehsan Khodapanah Aghdam, Reza Azad, Maral Zarvani +1
Melanoma is caused by the abnormal growth of melanocytes in human skin. Like other cancers, this life-threatening skin cancer can be treated with early diagnosis. To support a diag…
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…
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…
Medical Image Segmentation on MRI Images with Missing Modalities: A Review
Reza Azad, Nika Khosravi, Mohammad Dehghanmanshadi +2
Dealing with missing modalities in Magnetic Resonance Imaging (MRI) and overcoming their negative repercussions is considered a hurdle in biomedical imaging. The combination of a s…
Stacked Hourglass Network with a Multi-level Attention Mechanism: Where to Look for Intervertebral Disc Labeling
Reza Azad, Lucas Rouhier, Julien Cohen-Adad
Labeling vertebral discs from MRI scans is important for the proper diagnosis of spinal related diseases, including multiple sclerosis, amyotrophic lateral sclerosis, degenerative…
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…
Multi-level Context Gating of Embedded Collective Knowledge for Medical Image Segmentation
Maryam Asadi-Aghbolaghi, Reza Azad, Mahmood Fathy +1
Medical image segmentation has been very challenging due to the large variation of anatomy across different cases. Recent advances in deep learning frameworks have exhibited faster…
Bi-Directional ConvLSTM U-Net with Densley Connected Convolutions
Reza Azad, Maryam Asadi-Aghbolaghi, Mahmood Fathy +1
In recent years, deep learning-based networks have achieved state-of-the-art performance in medical image segmentation. Among the existing networks, U-Net has been successfully app…