Machine learning and deep learning for brain tumor MRI image segmentation
Brain tumors are often fatal. Therefore, accurate brain tumor image segmentation is critical
for the diagnosis, treatment, and monitoring of patients with these tumors. Magnetic …
for the diagnosis, treatment, and monitoring of patients with these tumors. Magnetic …
A deep learning based four-fold approach to classify brain MRI: BTSCNet
J Chaki, M Woźniak - Biomedical Signal Processing and Control, 2023 - Elsevier
Incorrect diagnosis of brain tumor types prevent appropriate response to medical assistance
and reduces patients' chances of survival. Examining MRI images of the patient's brain …
and reduces patients' chances of survival. Examining MRI images of the patient's brain …
MBANet: A 3D convolutional neural network with multi-branch attention for brain tumor segmentation from MRI images
Y Cao, W Zhou, M Zang, D An, Y Feng, B Yu - … Signal Processing and …, 2023 - Elsevier
More than half of brain tumors are malignant tumors, so there is a need for fast and accurate
segmentation of tumor regions in brain Magnetic Resonance Imaging (MRI) images …
segmentation of tumor regions in brain Magnetic Resonance Imaging (MRI) images …
A hybrid DenseNet121-UNet model for brain tumor segmentation from MR Images
Several techniques are used to detect brain tumors in the medical research field; however,
Magnetic Resonance Imaging (MRI) is still the most effective technique used by experts …
Magnetic Resonance Imaging (MRI) is still the most effective technique used by experts …
[HTML][HTML] Attention-based multimodal glioma segmentation with multi-attention layers for small-intensity dissimilarity
The segmentation of glioma by computer vision is one of the hot topics in medical image
analysis, which further helps doctors to make a better treatment plan for glioma. At present …
analysis, which further helps doctors to make a better treatment plan for glioma. At present …
A symmetrical approach to brain tumor segmentation in MRI using deep learning and threefold attention mechanism
Z Rahman, R Zhang, JA Bhutto - Symmetry, 2023 - mdpi.com
The symmetrical segmentation of brain tumor images is crucial for both clinical diagnosis
and computer-aided prognosis. Traditional manual methods are not only asymmetrical in …
and computer-aided prognosis. Traditional manual methods are not only asymmetrical in …
Uncertainty quantification and attention-aware fusion guided multi-modal MR brain tumor segmentation
T Zhou, S Zhu - Computers in Biology and Medicine, 2023 - Elsevier
Brain tumor is one of the most aggressive cancers in the world, accurate brain tumor
segmentation plays a critical role in clinical diagnosis and treatment planning. Although …
segmentation plays a critical role in clinical diagnosis and treatment planning. Although …
MPEDA-Net: A lightweight brain tumor segmentation network using multi-perspective extraction and dense attention
H Luo, D Zhou, Y Cheng, S Wang - Biomedical Signal Processing and …, 2024 - Elsevier
Malignant brain tumors are highly deadly, necessitating the quickly precise segmentation of
tumor regions. Previously, clinicians manually classified brain tumor regions utilizing …
tumor regions. Previously, clinicians manually classified brain tumor regions utilizing …
Multi-modal brain tumor segmentation via disentangled representation learning and region-aware contrastive learning
T Zhou - Pattern Recognition, 2024 - Elsevier
Brain tumors are threatening the life and health of people in the world. Automatic brain tumor
segmentation using multiple MR images is challenging in medical image analysis. It is …
segmentation using multiple MR images is challenging in medical image analysis. It is …
[PDF][PDF] SDS-Net: A lightweight 3D convolutional neural network with multi-branch attention for multimodal brain tumor accurate segmentation
Q Wu, Y Pei, Z Cheng, X Hu, C Wang - Math. Biosci. Eng, 2023 - aimspress.com
The accurate and fast segmentation method of tumor regions in brain Magnetic Resonance
Imaging (MRI) is significant for clinical diagnosis, treatment and monitoring, given the …
Imaging (MRI) is significant for clinical diagnosis, treatment and monitoring, given the …