DPAFNet: A residual dual-path attention-fusion convolutional neural network for multimodal brain tumor segmentation
Y Chang, Z Zheng, Y Sun, M Zhao, Y Lu… - … Signal Processing and …, 2023 - Elsevier
Brain tumors are highly hazardous, and precise automated segmentation of brain tumor
subregions has great importance and research significance on the diagnosis and treatment …
subregions has great importance and research significance on the diagnosis and treatment …
[HTML][HTML] DSRD-Net: Dual-stream residual dense network for semantic segmentation of instruments in robot-assisted surgery
T Mahmood, SW Cho, KR Park - Expert Systems with Applications, 2022 - Elsevier
In conventional robot-assisted minimally invasive procedures (RMIS), surgeons have narrow
visual and complex working spaces, along with specular reflection, blood, camera-lens …
visual and complex working spaces, along with specular reflection, blood, camera-lens …
Brain tumor segmentation of mri images using processed image driven u-net architecture
Brain tumor segmentation seeks to separate healthy tissue from tumorous regions. This is an
essential step in diagnosis and treatment planning to maximize the likelihood of successful …
essential step in diagnosis and treatment planning to maximize the likelihood of successful …
[PDF][PDF] Transforming healthcare with artificial intelligence in pakistan: a comprehensive overview
L Umer, MH Khan, Y Ayaz - Pakistan Armed Forces Medical Journal, 2023 - pafmj.org
Transforming Healthcare with Artificial Intelligence in Pakistan: A Comprehensive Overview
Page 1 Healthcare with Artificial Intelligence Pak Armed Forces Med J 2023; 73(4): 955 …
Page 1 Healthcare with Artificial Intelligence Pak Armed Forces Med J 2023; 73(4): 955 …
Brain Tumor Classification and Detection Based DL Models: A Systematic Review
In recent years, the realms of computer vision and deep learning have ushered in
transformative changes across various domains. Among these, deep learning stands out for …
transformative changes across various domains. Among these, deep learning stands out for …
Deep convolutional neural network with a multi-scale attention feature fusion module for segmentation of multimodal brain tumor
X He, W Xu, J Yang, J Mao, S Chen… - Frontiers in Neuroscience, 2021 - frontiersin.org
As a non-invasive, low-cost medical imaging technology, magnetic resonance imaging
(MRI) has become an important tool for brain tumor diagnosis. Many scholars have carried …
(MRI) has become an important tool for brain tumor diagnosis. Many scholars have carried …
AML‐Net: Attention‐based multi‐scale lightweight model for brain tumour segmentation in internet of medical things
M Zeeshan Aslam, B Raza, M Faheem… - CAAI Transactions on …, 2024 - Wiley Online Library
Brain tumour segmentation employing MRI images is important for disease diagnosis,
monitoring, and treatment planning. Till now, many encoder‐decoder architectures have …
monitoring, and treatment planning. Till now, many encoder‐decoder architectures have …
LSW-Net: A learning scattering wavelet network for brain tumor and retinal image segmentation
R Liu, H Nan, Y Zou, T Xie, Z Ye - Electronics, 2022 - mdpi.com
Convolutional network models have been widely used in image segmentation. However,
there are many types of boundary contour features in medical images which seriously affect …
there are many types of boundary contour features in medical images which seriously affect …
Effective data augmentation for brain tumor segmentation
This research is to propose a training strategy for 2D U‐Net is proposed that uses selective
data augmentation technique to overcome the class imbalance issue. This also helps in …
data augmentation technique to overcome the class imbalance issue. This also helps in …
Application of a pyramid pooling Unet model with integrated attention mechanism and Inception module in pancreatic tumor segmentation
Z Zhang, H Tian, Z Xu, Y Bian… - Journal of Applied Clinical …, 2023 - Wiley Online Library
Background The segmentation and recognition of pancreatic tumors are crucial tasks in the
diagnosis and treatment of pancreatic diseases. However, due to the relatively small …
diagnosis and treatment of pancreatic diseases. However, due to the relatively small …