Efficient Framework for Identifying, Locating, Detecting and Classifying MRI Brain Tumor in MRI Images.
Image processing has plays vital role in today's technological world. It can be applied in numerous application areas such as medical, remote sensing, computer vision etc. Brain tumor is caused due to formation of abnormal tissues within human brain. Therefore, it is necessary to remove affected tum...
| Publicado en: | Journal of Medical Systems Vol. 43; no. 7; pp. 1 - 15 |
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| Autores principales: | , |
| Formato: | diagnostic images equations & formulas pictorial research Journal Article |
| Publicado: |
Springer Nature
Jul2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=137182914&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 137182914 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Jul2019 vid: 43 iid: 7 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 137182914 137182914 137182914 10.1007/s10916-019-1253-1 137182914 ppf: 1 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Efficient Framework for Identifying, Locating, Detecting and Classifying MRI Brain Tumor in MRI Images. aug: au: Pandiselvi, T. Maheswaran, R. affil: Department of ECE, Kamaraj College of Engineering and Technology, Virudhunagar, Tamilnadu, India sug: subj: Brain Neoplasms Diagnosis Brain Neoplasms Classification Magnetic Resonance Imaging Methods Image Processing, Computer Assisted Methods Image Enhancement Algorithms Utilization Brain Anatomy and Histology Mathematics Automation Quality Control (Technology) ab: Image processing has plays vital role in today's technological world. It can be applied in numerous application areas such as medical, remote sensing, computer vision etc. Brain tumor is caused due to formation of abnormal tissues within human brain. Therefore, it is necessary to remove affected tumor part from the brain securely. Among various medical imaging techniques Magnetic Resonance Imaging (MRI) employs a vital role to generate images of internal parts of human body. Image segmentation is one of the challenging tasks in today's medical field. An effective segmentation using MRI slices can help to identifying the tumor with its actual size and shape. To meet this requirement, a novel method called Adaptive Convex Region Contour (ACRC) algorithm is presented. Here, Support Vector Machine (SVM) is utilized for slice classification whether it is normal or abnormal. After obtaining SVM results, abnormal slices are involved in segmentation process. Since, human body is having complicated 3D anatomical structure naturally. Unfortunately, MRI slices are yields only 2Dimensional images. The actual shape of tumor cannot be clearly visualized in 2D form. Hence, transformation from 2D to 3D is essential which helps the doctors during surgery. The Rapid Mode Image Matching (RMIM) algorithm has to be followed for 3D reconstruction modeling. After building 3D model, the original volume of the tumor is estimated. The precise experimentation was implemented in MATLAB simulation environment. The obtained results are confirmed that proposed method has better accurate results compared to existing methods. pubtype: Academic Journal doctype: diagnostic images equations & formulas pictorial research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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