27 citations · 86 across the 22 of their papers we have counts for
10 papers · 1 filter
A Novel Momentum-Based Deep Learning Techniques for Medical Image Classification and Segmentation
Koushik Biswas, Ridal Pal, Shaswat Patel +10
Accurately segmenting different organs from medical images is a critical prerequisite for computer-assisted diagnosis and intervention planning. This study proposes a deep learning…
The 2024 Brain Tumor Segmentation (BraTS) Challenge: Glioma Segmentation on Post-treatment MRI
Maria Correia de Verdier, Rachit Saluja, Louis Gagnon +82
Gliomas are the most common malignant primary brain tumors in adults and one of the deadliest types of cancer. There are many challenges in treatment and monitoring due to the gene…
Analysis of the 2024 BraTS Meningioma Radiotherapy Planning Automated Segmentation Challenge
Dominic LaBella, Valeriia Abramova, Mehdi Astaraki +102
The 2024 Brain Tumor Segmentation Meningioma Radiotherapy (BraTS-MEN-RT) challenge aimed to advance automated segmentation algorithms using the largest known multi-institutional da…
FuseNet: Self-Supervised Dual-Path Network for Medical Image Segmentation
Amirhossein Kazerouni, Sanaz Karimijafarbigloo, Reza Azad +3
Semantic segmentation, a crucial task in computer vision, often relies on labor-intensive and costly annotated datasets for training. In response to this challenge, we introduce Fu…
Leveraging Unlabeled Data for 3D Medical Image Segmentation through Self-Supervised Contrastive Learning
Sanaz Karimijafarbigloo, Reza Azad, Yury Velichko +2
Current 3D semi-supervised segmentation methods face significant challenges such as limited consideration of contextual information and the inability to generate reliable pseudo-la…
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…
Self-supervised Semantic Segmentation: Consistency over Transformation
Sanaz Karimijafarbigloo, Reza Azad, Amirhossein Kazerouni +3
Accurate medical image segmentation is of utmost importance for enabling automated clinical decision procedures. However, prevailing supervised deep learning approaches for medical…
Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentation
Reza Azad, Leon Niggemeier, Michael Huttemann +5
Medical image segmentation has seen significant improvements with transformer models, which excel in grasping far-reaching contexts and global contextual information. However, the…
Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture Detection
Reza Azad, Amirhossein Kazerouni, Babak Azad +4
Vision Transformer (ViT) models have demonstrated a breakthrough in a wide range of computer vision tasks. However, compared to the Convolutional Neural Network (CNN) models, it ha…
The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma
Dominic LaBella, Maruf Adewole, Michelle Alonso-Basanta +57
Meningiomas are the most common primary intracranial tumor in adults and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists,…