Towards Reinforced Brain Tumor Segmentation on MRI Images Based on Temperature Changes on Pathologic Area.
Brain tumor segmentation is the process of separating the tumor from normal brain tissues; in clinical routine, it provides useful information for diagnosis and treatment planning. However, it is still a challenging task due to the irregular form and confusing boundaries of tumors. Tumor cells therm...
| Publicado en: | International Journal of Biomedical Imaging pp. 1 - 19 |
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| Autores principales: | , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
3/3/2019
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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=135031691&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 135031691 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16874188 1WZI jtl: International Journal of Biomedical Imaging issn: 16874188 maglogo: N pubinfo: dt: 3/3/2019 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 135031691 135031691 135031691 10.1155/2019/1758948 135031691 ppf: 1 ppct: 18 formats: tig: atl: Towards Reinforced Brain Tumor Segmentation on MRI Images Based on Temperature Changes on Pathologic Area. aug: au: Bousselham, Abdelmajid Bouattane, Omar Youssfi, Mohamed Raihani, Abdelhadi affil: SSDIA Laboratory, ENSET Mohammedia University Hassan 2, Casablanca, Morocco sug: subj: Brain Neoplasms Diagnosis Magnetic Resonance Imaging Methods Body Temperature Changes False Negative Results False Positive Results Human Brain Neoplasms Pathology Contrast Media ab: Brain tumor segmentation is the process of separating the tumor from normal brain tissues; in clinical routine, it provides useful information for diagnosis and treatment planning. However, it is still a challenging task due to the irregular form and confusing boundaries of tumors. Tumor cells thermally represent a heat source; their temperature is high compared to normal brain cells. The main aim of the present paper is to demonstrate that thermal information of brain tumors can be used to reduce false positive and false negative results of segmentation performed in MRI images. Pennes bioheat equation was solved numerically using the finite difference method to simulate the temperature distribution in the brain; Gaussian noises of ±2% were added to the simulated temperatures. Canny edge detector was used to detect tumor contours from the calculated thermal map, as the calculated temperature showed a large gradient in tumor contours. The proposed method is compared to Chan–Vese based level set segmentation method applied to T1 contrast-enhanced and Flair MRI images of brains containing tumors with ground truth. The method is tested in four different phantom patients by considering different tumor volumes and locations and 50 synthetic patients taken from BRATS 2012 and BRATS 2013. The obtained results in all patients showed significant improvement using the proposed method compared to segmentation by level set method with an average of 0.8% of the tumor area and 2.48% of healthy tissue was differentiated using thermal images only. We conclude that tumor contours delineation based on tumor temperature changes can be exploited to reinforce and enhance segmentation algorithms in MRI diagnostic. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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