CM-SegNet: A deep learning-based automatic segmentation approach for medical images by combining convolution and multilayer perceptron
Accurate segmentation of lesions in medical images is of great significance for clinical
diagnosis and evaluation. The low contrast between lesions and surrounding tissues …
diagnosis and evaluation. The low contrast between lesions and surrounding tissues …
[HTML][HTML] 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 …
IBA-U-Net: Attentive BConvLSTM U-Net with redesigned inception for medical image segmentation
S Chen, Y Zou, PX Liu - Computers in Biology and Medicine, 2021 - Elsevier
Accurate segmentation of medical images plays an essential role in their analysis and has a
wide range of research and application values in fields of practice such as medical research …
wide range of research and application values in fields of practice such as medical research …
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 …
MHSU-Net: A more versatile neural network for medical image segmentation
H Ma, Y Zou, PX Liu - Computer Methods and Programs in Biomedicine, 2021 - Elsevier
Background and objective: Medical image segmentation plays an important role in clinic.
Recently, with the development of deep learning, many convolutional neural network (CNN) …
Recently, with the development of deep learning, many convolutional neural network (CNN) …
DMCNN: a deep multiscale convolutional neural network model for medical image segmentation
L Teng, H Li, S Karim - Journal of Healthcare Engineering, 2019 - Wiley Online Library
Medical image segmentation is one of the hot issues in the related area of image
processing. Precise segmentation for medical images is a vital guarantee for follow‐up …
processing. Precise segmentation for medical images is a vital guarantee for follow‐up …
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 …
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 …
An evolutionary DenseRes deep convolutional neural network for medical image segmentation
The performance of a Convolutional Neural Network (CNN) highly depends on its
architecture and corresponding parameters. Manually designing a CNN is a time-consuming …
architecture and corresponding parameters. Manually designing a CNN is a time-consuming …
[HTML][HTML] Two-layer Ensemble of Deep Learning Models for Medical Image Segmentation
One of the most important areas in medical image analysis is segmentation, in which raw
image data is partitioned into structured and meaningful regions to gain further insights. By …
image data is partitioned into structured and meaningful regions to gain further insights. By …