Abstract
Differentiation of glioblastoma multiformes (GBMs) and lymphomas using multi-sequence magnetic resonance imaging (MRI) is an important task that is valuable for treatment planning. However, this task is a challenge because GBMs and lymphomas may have a similar appearance in MRI images. This similarity may lead to misclassification and could affect the treatment results. In this paper, we propose a semi-automatic method based on multi-sequence MRI to differentiate these two types of brain tumors. Our method consists of three steps: 1) the key slice is selected from 3D MRIs and region of interests (ROIs) are drawn around the tumor region; 2) different features are extracted based on prior clinical knowledge and validated using a t-test; and 3) features that are helpful for classification are used to build an original feature vector and a support vector machine is applied to perform classification. In total, 58 GBM cases and 37 lymphoma cases are used to validate our method. A leave-one-out crossvalidation strategy is adopted in our experiments. The global accuracy of our method was determined as 96.84%, which indicates that our method is effective for the differentiation of GBM and lymphoma and can be applied in clinical diagnosis.
Keywords: Feature extraction, glioblastoma, lymphoma, support vector machine.
CNS & Neurological Disorders - Drug Targets
Title:Differentiation of Glioblastoma and Lymphoma Using Feature Extraction and Support Vector Machine
Volume: 16 Issue: 2
Author(s): Zhangjing Yang, Piaopiao Feng, Tian Wen, Minghua Wan and Xunning Hong
Affiliation:
Keywords: Feature extraction, glioblastoma, lymphoma, support vector machine.
Abstract: Differentiation of glioblastoma multiformes (GBMs) and lymphomas using multi-sequence magnetic resonance imaging (MRI) is an important task that is valuable for treatment planning. However, this task is a challenge because GBMs and lymphomas may have a similar appearance in MRI images. This similarity may lead to misclassification and could affect the treatment results. In this paper, we propose a semi-automatic method based on multi-sequence MRI to differentiate these two types of brain tumors. Our method consists of three steps: 1) the key slice is selected from 3D MRIs and region of interests (ROIs) are drawn around the tumor region; 2) different features are extracted based on prior clinical knowledge and validated using a t-test; and 3) features that are helpful for classification are used to build an original feature vector and a support vector machine is applied to perform classification. In total, 58 GBM cases and 37 lymphoma cases are used to validate our method. A leave-one-out crossvalidation strategy is adopted in our experiments. The global accuracy of our method was determined as 96.84%, which indicates that our method is effective for the differentiation of GBM and lymphoma and can be applied in clinical diagnosis.
Export Options
About this article
Cite this article as:
Yang Zhangjing, Feng Piaopiao, Wen Tian, Wan Minghua and Hong Xunning, Differentiation of Glioblastoma and Lymphoma Using Feature Extraction and Support Vector Machine, CNS & Neurological Disorders - Drug Targets 2017; 16 (2) . https://dx.doi.org/10.2174/1871527315666161018122909
DOI https://dx.doi.org/10.2174/1871527315666161018122909 |
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
-
Immunosuppressive Therapies in Solid Organ Transplantation
Immunology, Endocrine & Metabolic Agents in Medicinal Chemistry (Discontinued) MicroRNAs in Cancer: Small Molecules, Big Chances
Anti-Cancer Agents in Medicinal Chemistry Designed Multiple Ligands: Basic Research vs Clinical Outcomes
Current Medicinal Chemistry Design of Self-Immolative Linkers for Tumour-Activated Prodrug Therapy
Anti-Cancer Agents in Medicinal Chemistry Retinoid Receptors in Inflammatory Responses: A Potential Target for Pharmacology
Current Drug Targets - Inflammation & Allergy Current View on the Mechanism of Action of Perifosine in Cancer
Anti-Cancer Agents in Medicinal Chemistry Quantitative Structure-Activity Relationship Studies: Understanding the Mechanism of Tyrosine Kinase Inhibition
Current Enzyme Inhibition Nanosuspensions - An Update on Recent Patents, Methods of Preparation, and Evaluation Parameters
Recent Patents on Nanotechnology The Roles of Sox Family Genes in Sarcoma
Current Drug Targets Thiopurine S-Methyltransferase as a Pharmacogenetic Biomarker: Significance of Testing and Review of Major Methods
Cardiovascular & Hematological Agents in Medicinal Chemistry Angiogenesis in Chronic Lymphocytic Leukemia
Current Angiogenesis (Discontinued) Natural and Synthetic Furanocoumarins as Treatment for Vitiligo and Psoriasis
Current Drug Therapy Incidence and Management of Carfilzomib-induced Cardiovascular Toxicity; A Systematic Review and Meta-analysis
Cardiovascular & Hematological Disorders-Drug Targets Pharma-metabolomics in Neonatology: is it a Dream or a Fact?
Current Pharmaceutical Design Targeting Molecular Imaging of Breast Cancer by Radioimmunodetection Method in Nuclear Medicine
Current Molecular Imaging (Discontinued) The Proteasome as a Therapeutic Target for Lung Fibrosis
Current Enzyme Inhibition PEGylated Peptide-Based Imaging Agents for Targeted Molecular Imaging
Current Protein & Peptide Science Abscopal Effect of Radiation Therapy and Signal Transduction
Current Signal Transduction Therapy Editorial [Hot Topic: Recombinant Immunotoxins – The Next Generation (Executive Editor: Stefan Barth)]
Current Pharmaceutical Design Practical Approach to Children Presenting with Eosinophila and Hypereosinophilia
Current Pediatric Reviews