Diagnostic Method of Liver Cirrhosis Based on MR Image Texture Feature Extraction and Classification Algorithm.
In order to improve the accuracy of cirrhosis staging diagnosis based on MR images, a diagnostic method combining image texture feature extraction and classification algorithm is proposed. Firstly, the liver MR image is preprocessed, the region of interest (ROI) image patch is extracted therefrom, a...
| Publicado en: | Journal of Medical Systems Vol. 44; no. 1; pp. 1 - 9 |
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| Autores principales: | , , , |
| Formato: | diagnostic images equations & formulas pictorial tables/charts Journal Article |
| Publicado: |
Springer Nature
Jan2020
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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=141026252&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 141026252 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Jan2020 vid: 44 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 141026252 141026252 141026252 10.1007/s10916-019-1508-x 141026252 ppf: 1 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Diagnostic Method of Liver Cirrhosis Based on MR Image Texture Feature Extraction and Classification Algorithm. aug: au: chunmei, Xiong mei, Han yan, Zhao haiying, Wang affil: Department of Radiology, Jinan Infectious Disease Hospital affiliated to Shandong University, 250021, Jinan, Shandong, China sug: subj: Magnetic Resonance Imaging Methods Liver Cirrhosis Diagnosis Liver Cirrhosis Classification Image Processing, Computer Assisted Methods Algorithms Data Analysis, Statistical Image Enhancement Methods ab: In order to improve the accuracy of cirrhosis staging diagnosis based on MR images, a diagnostic method combining image texture feature extraction and classification algorithm is proposed. Firstly, the liver MR image is preprocessed, the region of interest (ROI) image patch is extracted therefrom, and the ROI image is quantized and compressed by the Lloyd algorithm. Then, the ROI image is filtered by a local binary pattern (LBP) operator, and then the texture feature of a 20-dimensional gray-level co-occurrence Matrix (GLCM) in four directions on the LBP image is extracted. Finally, MR image is classified by performing support vector machine (SVM) and the final diagnosis of liver cirrhosis is obtained. The experimental results show that the proposed method can accurately diagnose liver cirrhosis. pubtype: Academic Journal doctype: diagnostic images equations & formulas pictorial tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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