Anatomy|aided deep learning for medical image segmentation

Anatomy-aided deep learning for medical image segmentation

Anatomy-aided deep learning for medical image segmentation: a review, Lu Liu, Jelmer M Wolterink, Christoph Brune, Raymond N J Veldhuis.

Anatomy-aided deep learning for medical image segmentation

Deep learning (DL) has become widely used for medical image segmentation in recent years. However, despite these advances, there are still ...

Anatomy-aided deep learning for medical image segmentation

Deep learning (DL) has become widely used for medical image segmentation in recent years. However, despite these advances, there are still problems for which DL ...

Anatomy-aided deep learning for medical image segmentation

With LS representation,. the active contour model (ACM)is widely used for image segmentation. ... thresholding, region-growing, or edge detection, ...

Anatomy-aided deep learning for medical image segmentation

A review of anatomy-aided DL for medical image segmentation which covers systematically summarized anatomical information categories and ...

Anatomy-aided deep learning for medical image segmentation with ...

This thesis emphasizes the integration of anatomical information, particularly the shape of the pericardium, into segmentation methodologies.

Deep learning for medical image segmentation: State-of-the-art ...

In medical imaging, DL models are used in medical imaging to segment tissues and organs, which aids in illness diagnosis and treatment planning. DL-based image ...

Annotation-efficient deep learning for automatic medical image ...

Automatic medical image segmentation plays a critical role in scientific research and medical care. Existing high-performance deep learning ...

Deep learning and its application to medical image segmentation

... anatomy across different patients. However, recent advances in deep learning have made it possible to significantly improve the performance ...

Object recognition in medical images via anatomy-guided deep ...

Abstract. Purpose: Despite advances in deep learning, robust medical image segmentation in the presence of artifacts, pathology, and other imaging shortcomings ...

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.

Medical image segmentation using deep learning: A survey

This review summarises the progress of machine learning and deep learning in medical image registration, anatomy and cell structure detection, ...

Advancing Medical Image Segmentation with Mini-Net - arXiv

[18] aims to perform retinal vessel segmentation using a deep-supervised neural network with short connections. The model employs a deeply ...

[PDF] Deep Learning Techniques for Medical Image Segmentation

A critical appraisal of popular methods that have employed deep learning techniques for medical image segmentation is presented and the most common ...

Anatomy-Aided Deep Learning for Medical Image Segmentation

Anatomy-aided DL for medical image segmentation which covers systematically summarized anatomical information categories and corresponding representation ...

Deep Learning for Medical Image Segmentation - IGI Global

Pixel accurate 2-D, 3-D medical image segmentation to identify abnormalities for further analysis is on high demand for computer-aided medical imaging ...

A Review of Deep-Learning-Based Medical Image Segmentation ...

With the rapid development of deep learning, medical image processing based on deep convolutional neural networks has become a research hotspot. This paper ...

Detection-aided medical image segmentation using deep learning

We have used Convolutional Neural Networks (CNNs), that have proven good results in a variety of tasks, including medical imaging. The network to segment the ...

Deep Learning Techniques for Medical Image Segmentation

Deep learning-based image segmentation is by now firmly established as a robust tool in image segmentation. It has been widely used to ...

A review of deep learning based methods for medical image multi ...

End-to-end segmentation includes FCN, R-FCN, GAN and synthetic image-aided. •. Benchmark of algorithms' performances for thoracic and head-neck CT segmentation.