Academic Articles & Research Papers

Volume Segmentation of Liver and Liver Tumor with Fusion of Multi-Branch Features

The overcomplete convolutional structure for biological images and volume segmentation is an excellent solution to the problem in which traditional codec methods cannot accurately segment the boundary regions. Although such methods perform ...

A Deep Learning Harmonization of Multi-Vendor MRI for Robust Intervertebral Disc Segmentation

Magnetic resonance imaging (MRI) provides enhanced soft tissue contrast and high spatial resolution. However, the relationship between intensity values among soft tissues in MRI is inconsistent, even when obtained under the same conditions ...

TransCat: a hybrid CNN-transformer network with KAN for medical image segmentation

Medical image segmentation is a fundamental task in computer vision and plays an important role in clinical diagnosis and treatment planning. Existing methods are mainly built on either convolutional neural networks (CNNs) or Transformer-ba...

Enhancing medical image segmentation with HCE-Net: A heterogeneous feature collaborative extraction network.

Medical image segmentation using deep learning: A survey

Abstract Deep learning has been widely used for medical image segmentation and a large number of papers has been presented recording the success of deep learning in the field. A comprehensive thematic survey on medical image segmentation us...

Deep learning approaches to biomedical image segmentation

The review covers automatic segmentation of images by means of deep learning approaches in the area of medical imaging. Current developments in machine learning, particularly related to deep learning, are proving instrumental in identificat...