Automated brain tumour segmentation techniques—a review
M Angulakshmi… - International Journal of …, 2017 - Wiley Online Library
Automatic segmentation of brain tumour is the process of separating abnormal tissues from
normal tissues, such as white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) …
normal tissues, such as white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) …
State-of-the-art methods for brain tissue segmentation: A review
Brain tissue segmentation is one of the most sought after research areas in medical image
processing. It provides detailed quantitative brain analysis for accurate disease diagnosis …
processing. It provides detailed quantitative brain analysis for accurate disease diagnosis …
A survey on brain tumor detection techniques for MR images
PK Chahal, S Pandey, S Goel - Multimedia Tools and Applications, 2020 - Springer
One of the most crucial tasks in any brain tumor detection system is the isolation of abnormal
tissues from normal brain tissues. Interestingly, domain of brain tumor analysis has …
tissues from normal brain tissues. Interestingly, domain of brain tumor analysis has …
Unsupervised brain tumor segmentation using a symmetric-driven adversarial network
The aim of this study was to computationally model, in an unsupervised manner, a manifold
of symmetry variations in normal brains, such that the learned manifold can be used to …
of symmetry variations in normal brains, such that the learned manifold can be used to …
Accelerating compute intensive medical imaging segmentation algorithms using hybrid CPU-GPU implementations
Medical image processing is one of the most famous image processing fields in this era.
This fame comes because of the big revolution in information technology that is used to …
This fame comes because of the big revolution in information technology that is used to …
Brain structural disorders detection and classification approaches: a review
KR Bhatele, SS Bhadauria - Artificial Intelligence Review, 2020 - Springer
This paper is an effort to encapsulate the various developments in the domain of different
unsupervised, supervised and half supervised brain anomaly detection approaches or …
unsupervised, supervised and half supervised brain anomaly detection approaches or …
Characterisation of wellbore cement microstructure alteration under geologic carbon storage using X-ray computed micro-tomography: A framework for fast CT image …
X Miao, L Zhang, Y Wang, L Wang, X Fu, M Gan… - Cement and Concrete …, 2020 - Elsevier
An aqueous CO 2–cement interaction experiment along with X-ray computed micro-
tomography characterisation of pre-and post-exposure cement samples was carried out to …
tomography characterisation of pre-and post-exposure cement samples was carried out to …
Image segmentation and bias correction using local inhomogeneous iNtensity clustering (LINC): A region-based level set method
C Feng, D Zhao, M Huang - Neurocomputing, 2017 - Elsevier
Image segmentation is still an open problem due to the existing of intensity inhomogeneity
and noise. To accurately segment images with these biases, a local inhomogeneous …
and noise. To accurately segment images with these biases, a local inhomogeneous …
Machine learning to empower electrohydrodynamic processing
Electrohydrodynamic (EHD) processes are promising healthcare fabrication technologies,
as evidenced by the number of commercialised and food-and-drug administration (FDA) …
as evidenced by the number of commercialised and food-and-drug administration (FDA) …
Image fusion incorporating parameter estimation optimized Gaussian mixture model and fuzzy weighted evaluation system: A case study in time-series plantar …
The key issue in image fusion is the process of defining evaluation indices for the output
image and for multi-scale image data set. This paper attempted to develop a fusion model …
image and for multi-scale image data set. This paper attempted to develop a fusion model …