Coronary Calcium Detection Based on Improved Deep Residual Network in Mimics.
Coronary calcium detection in medicine image processing is a hot research topic. According to the low resolution and complex background in medicine image, an improved coronary calcium detection algorithm based on the Single Shot MultiBox Detector (SSD) in Mimics is proposed in this paper. The algori...
| Publicado en: | Journal of Medical Systems Vol. 43; no. 5 |
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| Autores principales: | , , , , , |
| Formato: | equations & formulas tables/charts Journal Article |
| Publicado: |
Springer Nature
May2019
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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=136129194&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 136129194 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: May2019 vid: 43 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 136129194 136129194 136129194 10.1007/s10916-019-1218-4 136129194 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Coronary Calcium Detection Based on Improved Deep Residual Network in Mimics. aug: au: Datong, Chen Minghui, Liang Cheng, Jin Yue, Sun Dongbin, Xu Yueming, Lin affil: School of Medical Technology, Qiqihar Medical University, 161006, Qiqihar, Heilongjiang, China sug: subj: Calcium Analysis Coronary Stenosis Diagnosis Algorithms Neural Networks (Computer) Methods Image Processing, Computer Assisted Models, Structural Tomography, X-Ray Computed Quality Improvement Learning ab: Coronary calcium detection in medicine image processing is a hot research topic. According to the low resolution and complex background in medicine image, an improved coronary calcium detection algorithm based on the Single Shot MultiBox Detector (SSD) in Mimics is proposed in this paper. The algorithm firstly uses the aggregate channel feature model to preprocess the image to obtain the suspected calcium area, which greatly reduces the time of single-frame image detection. The basic network VGG-16 is replaced by Resnet-50, which introduces the identity mapping to solve the problem of reducing the detection accuracy when the number of network layers are increased. Finally, the powerful and flexible two-parameter loss function is used to optimize the training deep network and improve the network model generalization ability. Qualitative and quantitative experiments show that the performance of the proposed detection algorithm exceeds the existing calcium detection algorithms, and the detection efficiency is improved while ensuring the accuracy of calcium detection. pubtype: Academic Journal doctype: equations & formulas tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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