[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 …
State-of-the-art techniques using pre-operative brain MRI scans for survival prediction of glioblastoma multiforme patients and future research directions
Objective Glioblastoma multiforme (GBM) is a grade IV brain tumour with very low life
expectancy. Physicians and oncologists urgently require automated techniques in clinics for …
expectancy. Physicians and oncologists urgently require automated techniques in clinics for …
Overall survival prediction for gliomas using a novel compound approach
H Huang, W Zhang, Y Fang, J Hong, S Su… - Frontiers in …, 2021 - frontiersin.org
As a highly malignant tumor, the incidence and mortality of glioma are not optimistic.
Predicting the survival time of patients with glioma by extracting the feature information from …
Predicting the survival time of patients with glioma by extracting the feature information from …
Interpretable machine learning model to predict survival days of malignant brain tumor patients
An artificial intelligence (AI) model's performance is strongly influenced by the input features.
Therefore, it is vital to find the optimal feature set. It is more crucial for the survival prediction …
Therefore, it is vital to find the optimal feature set. It is more crucial for the survival prediction …
Prediction of survival of glioblastoma patients using local spatial relationships and global structure awareness in FLAIR MRI brain images
This article introduces a framework for predicting the survival of brain tumor patients by
analyzing magnetic resonance images. The prediction of brain tumor survival is challenging …
analyzing magnetic resonance images. The prediction of brain tumor survival is challenging …
[HTML][HTML] A triplanar ensemble model for brain tumor segmentation with volumetric multiparametric magnetic resonance images
Automated segmentation methods can produce faster segmentation of tumors in medical
images, aiding medical professionals in diagnosis and treatment plans. A 3D U-Net method …
images, aiding medical professionals in diagnosis and treatment plans. A 3D U-Net method …
The multi-level classification network (MCN) with modified residual U-Net for ischemic stroke lesions segmentation from ATLAS
Ischemic and hemorrhagic strokes are two major types of internal brain injury. 3D brain MRI
is suggested by neurologists to examine the brain. Manual examination of brain MRI is very …
is suggested by neurologists to examine the brain. Manual examination of brain MRI is very …
VGG-UNET for brain tumor segmentation and ensemble model for survival prediction
Brain tumor is the spread of abnormal cells in the brain. Out of several kinds of brain tumor
gliomas is the most dangerous with low survival rate and difficult to detect manually due to …
gliomas is the most dangerous with low survival rate and difficult to detect manually due to …
Multi-view brain tumor segmentation (MVBTS): An ensemble of planar and triplanar attention UNets
Abstract 3D UNet has achieved high brain tumor segmentation performance but requires
high computation, large memory, abundant training data, and has limited interpretability. As …
high computation, large memory, abundant training data, and has limited interpretability. As …
Non‐invasive prediction of overall survival time for glioblastoma multiforme patients based on multimodal MRI radiomics
Glioblastoma multiforme (GBM) is the most common and deadly primary malignant brain
tumor. As GBM tumor is aggressive and shows high biological heterogeneity, the overall …
tumor. As GBM tumor is aggressive and shows high biological heterogeneity, the overall …