Computer-aided diagnosis system for tissue characterization of brain tumor on magnetic resonance images

MP Arakeri, GRM Reddy - Signal, Image and Video Processing, 2015 - Springer
The manual analysis of brain tumor on magnetic resonance (MR) images is time-consuming
and subjective. Thus, to avoid human errors in brain tumor diagnosis, this paper presents an …

Brain tumor segmentation using cluster ensemble and deep super learner for classification of MRI

P Ramya, MS Thanabal, C Dharmaraja - Journal of Ambient Intelligence …, 2021 - Springer
The Accurate segmentation and classification takes place a major role in the medical image
processing to detect and locate the abnormal tissue region. In this, the three different types …

Optimized multi threshold brain tumor image segmentation using two dimensional minimum cross entropy based on co-occurrence matrix

T Kaur, BS Saini, S Gupta - Medical Imaging in Clinical Applications …, 2016 - Springer
The present chapter proposes an automatic segmentation method that performs multilevel
image thresholding by using the spatial information encoded in the gray level co-occurrence …

A novel content-based active contour model for brain tumor segmentation

J Sachdeva, V Kumar, I Gupta, N Khandelwal… - Magnetic resonance …, 2012 - Elsevier
Brain tumor segmentation is a crucial step in surgical and treatment planning. Intensity-
based active contour models such as gradient vector flow (GVF), magneto static active …

An unsupervised learning method with a clustering approach for tumor identification and tissue segmentation in magnetic resonance brain images

G Vishnuvarthanan, MP Rajasekaran, P Subbaraj… - Applied Soft …, 2016 - Elsevier
Malignant and benign types of tumor infiltrated in human brain are diagnosed with the help
of an MRI scanner. With the slice images obtained using an MRI scanner, certain image …

Simulation of brain tumors in MR images for evaluation of segmentation efficacy

M Prastawa, E Bullitt, G Gerig - Medical image analysis, 2009 - Elsevier
Obtaining validation data and comparison metrics for segmentation of magnetic resonance
images (MRI) are difficult tasks due to the lack of reliable ground truth. This problem is even …

Brain tumors detection and segmentation in MR images: Gabor wavelet vs. statistical features

N Nabizadeh, M Kubat - Computers & Electrical Engineering, 2015 - Elsevier
Automated recognition of brain tumors in magnetic resonance images (MRI) is a difficult
procedure owing to the variability and complexity of the location, size, shape, and texture of …

Multiclass brain tumor classification using region growing based tumor segmentation and ensemble wavelet features

G Latif, DNFA Iskandar, J Alghazo - Proceedings of the 2018 …, 2018 - dl.acm.org
In this research, an automated method is proposed for Brain tumor classification into four
different types which is an important step in brain tumor diagnosis. Most of the recent …

An improved Gabor wavelet transform and rough K-means clustering algorithm for MRI brain tumor image segmentation

DM Kumar, D Satyanarayana, MNG Prasad - Multimedia Tools and …, 2021 - Springer
Image processing is significant in the medical field which provides detailed information
about medical images and image segmentation is an essential part of medical image …

Entropy based segmentation of tumor from brain MR images–a study with teaching learning based optimization

V Rajinikanth, SC Satapathy, SL Fernandes… - Pattern Recognition …, 2017 - Elsevier
Image processing plays an important role in various medical applications to support the
computerized disease examination. Brain tumor, such as glioma is one of the life threatening …