Abstract
This paper presents an automatic classification system for segregating pathological brain from normal brains in magnetic resonance imaging scanning. The proposed system employs contrast limited adaptive histogram equalization scheme to enhance the diseased region in brain MR images. Two-dimensional stationary wavelet transform is harnessed to extract features from the preprocessed images. The feature vector is constructed using the energy and entropy values, computed from the level- 2 SWT coefficients. Then, the relevant and uncorrelated features are selected using symmetric uncertainty ranking filter. Subsequently, the selected features are given input to the proposed AdaBoost with support vector machine classifier, where SVM is used as the base classifier of AdaBoost algorithm. To validate the proposed system, three standard MR image datasets, Dataset-66, Dataset-160, and Dataset- 255 have been utilized. The 5 runs of k-fold stratified cross validation results indicate the suggested scheme offers better performance than other existing schemes in terms of accuracy and number of features. The proposed system earns ideal classification over Dataset-66 and Dataset-160; whereas, for Dataset- 255, an accuracy of 99.45% is achieved.
Keywords: AdaBoost with SVM, computer-aided diagnosis, contrast limited adaptive histogram equalization, magnetic resonance imaging, stationary wavelet transform.
CNS & Neurological Disorders - Drug Targets
Title:Stationary Wavelet Transform and AdaBoost with SVM Based Pathological Brain Detection in MRI Scanning
Volume: 16 Issue: 2
Author(s): Deepak Ranjan Nayak, Ratnakar Dash and Banshidhar Majhi
Affiliation:
Keywords: AdaBoost with SVM, computer-aided diagnosis, contrast limited adaptive histogram equalization, magnetic resonance imaging, stationary wavelet transform.
Abstract: This paper presents an automatic classification system for segregating pathological brain from normal brains in magnetic resonance imaging scanning. The proposed system employs contrast limited adaptive histogram equalization scheme to enhance the diseased region in brain MR images. Two-dimensional stationary wavelet transform is harnessed to extract features from the preprocessed images. The feature vector is constructed using the energy and entropy values, computed from the level- 2 SWT coefficients. Then, the relevant and uncorrelated features are selected using symmetric uncertainty ranking filter. Subsequently, the selected features are given input to the proposed AdaBoost with support vector machine classifier, where SVM is used as the base classifier of AdaBoost algorithm. To validate the proposed system, three standard MR image datasets, Dataset-66, Dataset-160, and Dataset- 255 have been utilized. The 5 runs of k-fold stratified cross validation results indicate the suggested scheme offers better performance than other existing schemes in terms of accuracy and number of features. The proposed system earns ideal classification over Dataset-66 and Dataset-160; whereas, for Dataset- 255, an accuracy of 99.45% is achieved.
Export Options
About this article
Cite this article as:
Nayak Ranjan Deepak, Dash Ratnakar and Majhi Banshidhar, Stationary Wavelet Transform and AdaBoost with SVM Based Pathological Brain Detection in MRI Scanning, CNS & Neurological Disorders - Drug Targets 2017; 16 (2) . https://dx.doi.org/10.2174/1871527315666161024142036
DOI https://dx.doi.org/10.2174/1871527315666161024142036 |
Print ISSN 1871-5273 |
Publisher Name Bentham Science Publisher |
Online ISSN 1996-3181 |
Call for Papers in Thematic Issues
Diagnosis and treatment of central nervous system infectious diseases
Infectious diseases of the central nervous system (CNS) can be divided into bacterial, tuberculous, viral, fungal, parasitic infections, etc. Early etiological treatment is often the most crucial means to reduce the mortality rate of patients with central nervous system infections, reduce complications and sequelae, and improve prognosis. The initial clinical ...read more
Techniques of Drug Repurposing: Delivering a new life to Herbs & Drugs
Of late, with the adaptation of innovative approaches and integration of advancements made towards medical sciences as well as the availability of a wide range of tools; several therapeutic challenges are being translated into viable clinical solutions, with a high degree of efficacy, safety, and selectivity. With a better understanding ...read more
Trends and perspectives in the rational management of CNS disorders
Central nervous system (CNS) diseases enforce a significant global health burden, driving ongoing efforts to improve our understanding and effectiveness of therapy. This issue investigates current advances in the discipline, focusing on the understanding as well as therapeutic handling of various CNS diseases. The issue covers a variety of diseases, ...read more
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
Related Articles
-
Nanocarriers for the Simultaneous Co-Delivery of Therapeutic Genes and Anticancer Drugs
Current Pharmaceutical Biotechnology RECKing MMP: Relevance of Reversion-inducing Cysteine-rich Protein with Kazal Motifs as a Prognostic Marker and Therapeutic Target for Cancer (A Review)
Anti-Cancer Agents in Medicinal Chemistry Meet Our Associate Editor
Current Bioactive Compounds Novel Anticancer Strategy Aimed at Targeting Shelterin Complexes by the Induction of Structural Changes in Telomeric DNA: Hitting two Birds with one Stone
Current Cancer Drug Targets Expanding Spectrum of Sodium Potassium Chloride Co-transporters in the Pathophysiology of Diseases
Current Neuropharmacology Continuous Nanostructures for the Controlled Release of Drugs
Current Pharmaceutical Design Peptide Targeted Copper-64 Radiopharmaceuticals
Current Topics in Medicinal Chemistry Drug Delivery Systems for Brain Tumor Therapy
Current Pharmaceutical Design Glutamate Transporter 1: Target for the Treatment of Alcohol Dependence
Current Medicinal Chemistry The Blood-Brain/Tumor Barriers: Challenges and Chances for Malignant Gliomas Targeted Drug Delivery
Current Pharmaceutical Biotechnology Regulating miRNA by Natural Agents as a New Strategy for Cancer Treatment
Current Drug Targets Irreversible Multitargeted ErbB Family Inhibitors for Therapy of Lung and Breast Cancer
Current Cancer Drug Targets Gold Nanoparticles - Synthesis and Applications in Cancer Management
Recent Patents on Materials Science The Role of 4-Thiazolidinone Scaffold in Targeting Variable Biomarkers and Pathways Involving Cancer
Anti-Cancer Agents in Medicinal Chemistry Stimuli-Responsive Nanoparticles for siRNA Delivery
Current Pharmaceutical Design Aquaporins and Roles in Brain Health and Brain Injury
Mini-Reviews in Medicinal Chemistry Molecular Pharmacology of Malignant Pleural Mesothelioma: Challenges and Perspectives From Preclinical and Clinical Studies
Current Drug Targets Release of Soluble Ligands for the Activating NKG2D Receptor: One More Immune Evasion Strategy Evolved by HIV-1 ?
Current Drug Targets Nanomedical Platform for Drug Delivery in Cancer
Current Organic Chemistry High Throughput Screening for Colorectal Cancer Specific Compounds
Combinatorial Chemistry & High Throughput Screening