Medical image segmentation using deep learning with feature enhancement
S Huang, M Huang, Y Zhang, J Chen… - IET Image …, 2020 - Wiley Online Library
Pre‐segmentation is known as a crucial step in medical image analysis. Many approaches
have been proposed to make improvement to both the quality and efficiency of …
have been proposed to make improvement to both the quality and efficiency of …
[HTML][HTML] Selecting the best optimizers for deep learning–based medical image segmentation
Purpose The goal of this work is to explore the best optimizers for deep learning in the
context of medical image segmentation and to provide guidance on how to design …
context of medical image segmentation and to provide guidance on how to design …
A review of deep-learning-based medical image segmentation methods
As an emerging biomedical image processing technology, medical image segmentation has
made great contributions to sustainable medical care. Now it has become an important …
made great contributions to sustainable medical care. Now it has become an important …
A novel deep learning model for medical image segmentation with convolutional neural network and transformer
Z Zhang, H Wu, H Zhao, Y Shi, J Wang, H Bai… - Interdisciplinary Sciences …, 2023 - Springer
Accurate segmentation of medical images is essential for clinical decision-making, and deep
learning techniques have shown remarkable results in this area. However, existing …
learning techniques have shown remarkable results in this area. However, existing …
Comparative review on traditional and deep learning methods for medical image segmentation
Medical image segmentation is a vital task in medical imaging, aiming to extract meaningful
and precise information from images. While traditional methods have been extensively used …
and precise information from images. While traditional methods have been extensively used …
Medical image segmentation using deep learning: A survey
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 …
papers has been presented recording the success of deep learning in the field. A …
DRU-Net: an efficient deep convolutional neural network for medical image segmentation
Residual network (ResNet) and densely connected network (DenseNet) have significantly
improved the training efficiency and performance of deep convolutional neural networks …
improved the training efficiency and performance of deep convolutional neural networks …
Deep supervision feature refinement attention network for medical image segmentation
Z Fu, J Li, Z Hua, L Fan - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
The improvement of medical technology is closely related to the development of computers.
Deep learning methods have become an important means for medical image processing …
Deep learning methods have become an important means for medical image processing …
[Retracted] Deep Neural Networks for Medical Image Segmentation
P Malhotra, S Gupta, D Koundal… - Journal of …, 2022 - Wiley Online Library
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 …
ConvUNeXt: An efficient convolution neural network for medical image segmentation
Recently, ConvNeXts constructing from standard ConvNet modules has produced
competitive performance in various image applications. In this paper, an efficient model …
competitive performance in various image applications. In this paper, an efficient model …