CiT-Net: Convolutional neural networks hand in hand with vision transformers for medical image segmentation
The hybrid architecture of convolutional neural networks (CNNs) and Transformer are very
popular for medical image segmentation. However, it suffers from two challenges. First …
popular for medical image segmentation. However, it suffers from two challenges. First …
Bea-net: body and edge aware network with multi-scale short-term concatenation for medical image segmentation
Medical image segmentation is indispensable for diagnosis and prognosis of many
diseases. To improve the segmentation performance, this study proposes a new 2D body …
diseases. To improve the segmentation performance, this study proposes a new 2D body …
RFPNet: Reorganizing feature pyramid networks for medical image segmentation
Z Wang, J Zhu, S Fu, S Mao, Y Ye - Computers in biology and medicine, 2023 - Elsevier
Medical image segmentation is a crucial step in clinical treatment planning. However,
automatic and accurate medical image segmentation remains a challenging task, owing to …
automatic and accurate medical image segmentation remains a challenging task, owing to …
A multi-attention and depthwise separable convolution network for medical image segmentation
Automatic medical image segmentation method is highly needed to help experts in lesion
segmentation. The deep learning technology emerging has profoundly driven the …
segmentation. The deep learning technology emerging has profoundly driven the …
Cold SegDiffusion: A novel diffusion model for medical image segmentation
Medical image segmentation is crucial in accurately identifying and delineating regions of
interest in medical images, which can inform the diagnosis and treatment of various …
interest in medical images, which can inform the diagnosis and treatment of various …
Shape prior-constrained deep learning network for medical image segmentation
P Zhang, Y Cheng, S Tamura - Computers in Biology and Medicine, 2024 - Elsevier
We propose a shape prior representation-constrained multi-scale features fusion
segmentation network for medical image segmentation, including training and testing …
segmentation network for medical image segmentation, including training and testing …
A Deformable Constraint Transport Network for Optimal Aortic Segmentation from CT Images
W Lin, Z Gao, H Liu, H Zhang - IEEE Transactions on Medical …, 2023 - ieeexplore.ieee.org
Aortic segmentation from computed tomography (CT) is crucial for facilitating aortic
intervention, as it enables clinicians to visualize aortic anatomy for diagnosis and …
intervention, as it enables clinicians to visualize aortic anatomy for diagnosis and …
Assembling a Learnable Mumford–Shah Type Model with Multigrid Technique for Image Segmentation
J Meng, W Guo, J Liu, M Yang - SIAM Journal on Imaging Sciences, 2024 - SIAM
The classical Mumford–Shah (MS) model has been successful in some medical image
segmentation tasks, providing segmentation results with smooth boundaries of objects …
segmentation tasks, providing segmentation results with smooth boundaries of objects …
ResDAC-Net: a novel pancreas segmentation model utilizing residual double asymmetric spatial kernels
The pancreas not only is situated in a complex abdominal background but is also
surrounded by other abdominal organs and adipose tissue, resulting in blurred organ …
surrounded by other abdominal organs and adipose tissue, resulting in blurred organ …
Shape-Guided Dual Consistency Semi-Supervised Learning Framework for 3-D Medical Image Segmentation
Popular semi-supervised 3-D medical image segmentation networks commonly suffer from
two limitations: First, the geometry shape constraint of targets is frequently disregarded …
two limitations: First, the geometry shape constraint of targets is frequently disregarded …