Diagnosis of Thyroid Nodules Based on Local Non-quantitative Multi-Directional Texture Descriptor with Rotation Invariant Characteristics for Ultrasound Image.
The traditional texture feature lacks the directional analysis of graphical element, so it could not better distinguish the thyroid nodule texture image formed by the rotation of graphical element. A non-quantifiable local feature is adopted in this paper to design a robust texture descriptor so as...
| Publicado en: | Journal of Medical Systems Vol. 43; no. 7 |
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| Autores principales: | , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jul2019
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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=137182965&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 137182965 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Jul2019 vid: 43 iid: 7 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 137182965 137182965 137182965 10.1007/s10916-019-1373-7 137182965 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Diagnosis of Thyroid Nodules Based on Local Non-quantitative Multi-Directional Texture Descriptor with Rotation Invariant Characteristics for Ultrasound Image. aug: au: Bi, Li Shuang, Zhang affil: The First Affiliated Hospital of Jinzhou Medical University, 121001, Jinzhou, Liaoning, China sug: subj: Thyroid Nodule Ultrasonography Image Processing, Computer Assisted Diagnosis, Computer Assisted Methods Human Algorithms Image Enhancement Logistic Regression ROC Curve Sensitivity and Specificity ab: The traditional texture feature lacks the directional analysis of graphical element, so it could not better distinguish the thyroid nodule texture image formed by the rotation of graphical element. A non-quantifiable local feature is adopted in this paper to design a robust texture descriptor so as to enhance the robustness of the texture classification in the rotation and scale changes, which can improve the diagnostic accuracy of thyroid nodules in ultrasound images. First of all, the concept of local feature with rotational symmetry is introduced. It is found that many rotation invariant local features are rotational symmetric to a certain degree. Therefore, we propose a novel local feature to describe the rotation invariant properties of the texture. In order to deal with the change of rotation and scale of ultrasound thyroid nodules in image, Pairwise rotation-invariant spatial context feature is adopted to analyze the texture feature, which can combine with the scale information without increasing the dimension of the local feature. The fadopted local features have strong robustness to rotation and gray intensity variation. The experimental results show that our proposed method outperforms the existing algorithms on thyroid ultrasound data sets, which greatly improve the Diagnosis accuracy of thyroid nodules. 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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