Robust Skull-Stripping Segmentation Based on Irrational Mask for Magnetic Resonance Brain Images.
This paper proposes a new method for simple, efficient, and robust removal of the non-brain tissues in MR images based on an irrational mask for filtration within a binary morphological operation framework. The proposed skull-stripping segmentation is based on two irrational 3 × 3 and 5 × 5 masks, h...
| Publicado en: | Journal of Digital Imaging Vol. 28; no. 6; pp. 738 - 748 |
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| Autores principales: | , , |
| Formato: | algorithm diagnostic images research tables/charts Journal Article |
| Publicado: |
Springer Nature
Dec2015
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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=110813328&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 110813328 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Dec2015 vid: 28 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 110813328 110813328 110813328 10.1007/s10278-015-9776-6 NLM25733013 PMC4636724 110813328 ppf: 738 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Robust Skull-Stripping Segmentation Based on Irrational Mask for Magnetic Resonance Brain Images. aug: au: Moldovanu, Simona Moraru, Luminița Biswas, Anjan affil: Department of Chemistry, Physics and Environment, Faculty of Sciences and Environment, Dunărea de Jos University of Galaţi, 47 Domnească St. 800008 Galaţi Romania sug: subj: Magnetic Resonance Imaging Skull Anatomy and Histology Image Processing, Computer Assisted Methods Brain Anatomy and Histology Prospective Studies kappa Statistic Algorithms Evaluation Validation Studies Sensitivity and Specificity Adult Middle Age Aged Aged, 80 and Over Female Male Human Funding Source Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Aged, 80 & over Female Male ab: This paper proposes a new method for simple, efficient, and robust removal of the non-brain tissues in MR images based on an irrational mask for filtration within a binary morphological operation framework. The proposed skull-stripping segmentation is based on two irrational 3 × 3 and 5 × 5 masks, having the sum of its weights equal to the transcendental number π value provided by the Gregory-Leibniz infinite series. It allows maintaining a lower rate of useful pixel loss. The proposed method has been tested in two ways. First, it has been validated as a binary method by comparing and contrasting with Otsu's, Sauvola's, Niblack's, and Bernsen's binary methods. Secondly, its accuracy has been verified against three state-of-the-art skull-stripping methods: the graph cuts method, the method based on Chan-Vese active contour model, and the simplex mesh and histogram analysis skull stripping. The performance of the proposed method has been assessed using the Dice scores, overlap and extra fractions, and sensitivity and specificity as statistical methods. The gold standard has been provided by two neurologist experts. The proposed method has been tested and validated on 26 image series which contain 216 images from two publicly available databases: the Whole Brain Atlas and the Internet Brain Segmentation Repository that include a highly variable sample population (with reference to age, sex, healthy/diseased). The approach performs accurately on both standardized databases. The main advantage of the proposed method is its robustness and speed. pubtype: Academic Journal doctype: algorithm diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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