Segmentation and grading of brain tumors on apparent diffusion coefficient images using self-organizing maps
C Vijayakumar, G Damayanti, R Pant… - … Medical Imaging and …, 2007 - Elsevier
An accurate computer-assisted method to perform segmentation of brain tumor on apparent
diffusion coefficient (ADC) images and evaluate its grade (malignancy state) has been …
diffusion coefficient (ADC) images and evaluate its grade (malignancy state) has been …
Segmentation of tumor and edema along with healthy tissues of brain using wavelets and neural networks
A Demirhan, M Törü, I Güler - IEEE journal of biomedical and …, 2014 - ieeexplore.ieee.org
Robust brain magnetic resonance (MR) segmentation algorithms are critical to analyze
tissues and diagnose tumor and edema in a quantitative way. In this study, we present a …
tissues and diagnose tumor and edema in a quantitative way. In this study, we present a …
Brain tumor classification using the diffusion tensor image segmentation (D-SEG) technique
Background There is an increasing demand for noninvasive brain tumor biomarkers to guide
surgery and subsequent oncotherapy. We present a novel whole-brain diffusion tensor …
surgery and subsequent oncotherapy. We present a novel whole-brain diffusion tensor …
MRI brain tumor detection methods using contourlet transform based on time adaptive self-organizing map
A Farzamnia, SH Hazaveh, SS Siadat… - IEEE Access, 2023 - ieeexplore.ieee.org
The brain is one of the most complex organs in the body, composed of billions of cells that
work together to ensure proper functioning. However, when cells divide in a disorderly …
work together to ensure proper functioning. However, when cells divide in a disorderly …
Feature extraction from MRI ADC images for brain tumor classification using machine learning techniques
Background Diffusion-weighted (DW) imaging is a well-recognized magnetic resonance
imaging (MRI) technique that is being routinely used in brain examinations in modern …
imaging (MRI) technique that is being routinely used in brain examinations in modern …
An Efficient Brain Tumor Segmentation Method Based on Adaptive Moving Self-Organizing Map and Fuzzy K-Mean Clustering
Brain tumors in Magnetic resonance image segmentation is challenging research. With the
advent of a new era and research into machine learning, tumor detection and segmentation …
advent of a new era and research into machine learning, tumor detection and segmentation …
Advance computer analysis of magnetic resonance imaging (MRI) for early brain tumor detection
Purpose The brain tumor grows inside the skull and interposes with regular brain
functioning. The tumor growth may possibly result in cancer at a later stage. The early …
functioning. The tumor growth may possibly result in cancer at a later stage. The early …
Machine learning based brain tumour segmentation on limited data using local texture and abnormality
S Bonte, I Goethals, R Van Holen - Computers in biology and medicine, 2018 - Elsevier
Brain tumour segmentation in medical images is a very challenging task due to the large
variety in tumour shape, position, appearance, scanning modalities and scanning …
variety in tumour shape, position, appearance, scanning modalities and scanning …
[PDF][PDF] Brain lesion segmentation using fuzzy C-means on diffusion-weighted imaging
This paper presents an automatic segmentation of brain lesions from diffusion-weighted
imaging (DWI) using Fuzzy C-Means (FCM) algorithm. The lesions are acute stroke, tumour …
imaging (DWI) using Fuzzy C-Means (FCM) algorithm. The lesions are acute stroke, tumour …
Image analysis for MRI based brain tumor detection and feature extraction using biologically inspired BWT and SVM
The segmentation, detection, and extraction of infected tumor area from magnetic resonance
(MR) images are a primary concern but a tedious and time taking task performed by …
(MR) images are a primary concern but a tedious and time taking task performed by …