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A weak edge estimation based multi-task neural network for OCT segmentation.
PLoS One
January 2025
School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China.
Optical Coherence Tomography (OCT) offers high-resolution images of the eye's fundus. This enables thorough analysis of retinal health by doctors, providing a solid basis for diagnosis and treatment. With the development of deep learning, deep learning-based methods are becoming more popular for fundus OCT image segmentation.
View Article and Find Full Text PDFAn ultrasound image segmentation method for thyroid nodules based on dual-path attention mechanism-enhanced UNet+.
BMC Med Imaging
December 2024
College of Information Science and Technology, Shihezi University, Shihezi, 832003, Xinjiang, China.
Purpose: This study aims to design an auxiliary segmentation model for thyroid nodules to increase diagnostic accuracy and efficiency, thereby reducing the workload of medical personnel.
Methods: This study proposes a Dual-Path Attention Mechanism (DPAM)-UNet++ model, which can automatically segment thyroid nodules in ultrasound images. Specifically, the model incorporates dual-path attention modules into the skip connections of the UNet++ network to capture global contextual information in feature maps.
Model-based CBCT scatter correction with dual-layer flat-panel detector.
Med Phys
December 2024
Research Center for Advanced Detection Materials and Medical Imaging Devices, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China.
Background: Recently, the popularity of dual-layer flat-panel detector (DL-FPD) based dual-energy cone-beam CT (CBCT) imaging has been increasing. However, the image quality of dual-energy CBCT remains constrained by the Compton scattered x-ray photons.
Purpose: The objective of this study is to develop a novel scatter correction method, named e-Grid, for DL-FPD based CBCT imaging.
Effective Detection of Cloud Masks in Remote Sensing Images.
Sensors (Basel)
December 2024
Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China.
Effective detection of the contours of cloud masks and estimation of their distribution can be of practical help in studying weather changes and natural disasters. Existing deep learning methods are unable to extract the edges of clouds and backgrounds in a refined manner when detecting cloud masks (shadows) due to their unpredictable patterns, and they are also unable to accurately identify small targets such as thin and broken clouds. For these problems, we propose MDU-Net, a multiscale dual up-sampling segmentation network based on an encoder-decoder-decoder.
View Article and Find Full Text PDFA dual nonsubsampled contourlet network for synthesis images and infrared thermal images denoising.
PeerJ Comput Sci
January 2024
School of Automation Engineering, Northeast Electric Power University, Jilin, China.
The most direct way to find the electrical switchgear fault is to use infrared thermal imaging technology for temperature measurement. However, infrared thermal imaging images are usually polluted by noise, and there are problems such as low contrast and blurred edges. To solve these problems, this article proposes a dual convolutional neural network model based on nonsubsampled contourlet transform (NSCT).
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