Level Set Image Feature Detection and Application in COVID-19 Image Feature Knowledge Detection.
Artificial intelligence (AI) scholars and mediciners have reported AI systems that accurately detect medical imaging and COVID-19 in chest images. However, the robustness of these models remains unclear for the segmentation of images with nonuniform density distribution or the multiphase target. The...
| Publicado en: | BioMed Research International pp. 1 - 15 |
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| Autores principales: | , , , |
| Formato: | diagnostic images equations & formulas research Journal Article |
| Publicado: |
Wiley-Blackwell
5/17/2023
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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=163800515&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 163800515 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 5/17/2023 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 163800515 163800515 163800515 10.1155/2023/1632992 163800515 ppf: 1 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Level Set Image Feature Detection and Application in COVID-19 Image Feature Knowledge Detection. aug: au: Ji, Dongsheng Liu, Yafeng Zhang, Qingyi Zheng, Wenjun affil: School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China sug: subj: COVID-19 Diagnostic Imaging Image Processing, Computer Assisted Artificial Intelligence Human Algorithms Sensitivity and Specificity Pathology, Clinical Machine Learning ab: Artificial intelligence (AI) scholars and mediciners have reported AI systems that accurately detect medical imaging and COVID-19 in chest images. However, the robustness of these models remains unclear for the segmentation of images with nonuniform density distribution or the multiphase target. The most representative one is the Chan-Vese (CV) image segmentation model. In this paper, we demonstrate that the recent level set (LV) model has excellent performance on the detection of target characteristics from medical imaging relying on the filtering variational method based on the global medical pathology facture. We observe that the capability of the filtering variational method to obtain image feature quality is better than other LV models. This research reveals a far-reaching problem in medical-imaging AI knowledge detection. In addition, from the analysis of experimental results, the algorithm proposed in this paper has a good effect on detecting the lung region feature information of COVID-19 images and also proves that the algorithm has good adaptability in processing different images. These findings demonstrate that the proposed LV method should be seen as an effective clinically adjunctive method using machine-learning healthcare models. pubtype: Academic Journal doctype: diagnostic images equations & formulas research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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