[Retracted] Deep Neural Networks for Medical Image Segmentation
Image segmentation is a branch of digital image processing which has numerous
applications in the field of analysis of images, augmented reality, machine vision, and many …
applications in the field of analysis of images, augmented reality, machine vision, and many …
U-net and its variants for medical image segmentation: A review of theory and applications
U-net is an image segmentation technique developed primarily for image segmentation
tasks. These traits provide U-net with a high utility within the medical imaging community …
tasks. These traits provide U-net with a high utility within the medical imaging community …
Unet++: Redesigning skip connections to exploit multiscale features in image segmentation
The state-of-the-art models for medical image segmentation are variants of U-Net and fully
convolutional networks (FCN). Despite their success, these models have two limitations:(1) …
convolutional networks (FCN). Despite their success, these models have two limitations:(1) …
Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19
Shortly after deep learning algorithms were applied to Image Analysis, and more importantly
to medical imaging, their applications increased significantly to become a trend. Likewise …
to medical imaging, their applications increased significantly to become a trend. Likewise …
Bridging 2D and 3D segmentation networks for computation-efficient volumetric medical image segmentation: An empirical study of 2.5 D solutions
Recently, deep convolutional neural networks have achieved great success for medical
image segmentation. However, unlike segmentation of natural images, most medical images …
image segmentation. However, unlike segmentation of natural images, most medical images …
Transformer-based 3D U-Net for pulmonary vessel segmentation and artery-vein separation from CT images
Transformer-based methods have led to the revolutionizing of multiple computer vision
tasks. Inspired by this, we propose a transformer-based network with a channel-enhanced …
tasks. Inspired by this, we propose a transformer-based network with a channel-enhanced …
AATSN: Anatomy Aware Tumor Segmentation Network for PET-CT volumes and images using a lightweight fusion-attention mechanism
Abstract Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) provides metabolic
information, while Computed Tomography (CT) provides the anatomical context of the …
information, while Computed Tomography (CT) provides the anatomical context of the …