Automatic Segmentation of Bone Canals in Histological Images.
The literature provides many works that focused on cell nuclei segmentation in histological images. However, automatic segmentation of bone canals is still a less explored field. In this sense, this paper presents a method for automatic segmentation approach to assist specialists in the analysis of...
| Published in: | Journal of Digital Imaging Vol. 34; no. 3; pp. 678 - 691 |
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| Main Authors: | , , , , , , |
| Format: | diagnostic images equations & formulas pictorial research tables/charts Journal Article |
| Published: |
Springer Nature
Jun2021
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=151702163&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 151702163 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Jun2021 vid: 34 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 151702163 150120593 151702163 151702163 10.1007/s10278-021-00454-1 151702163 ppf: 678 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Automatic Segmentation of Bone Canals in Histological Images. aug: au: Gondim, Pedro Henrique Campos Cunha Limirio, Pedro Henrique Justino Oliveira Rocha, Flaviana Soares Batista, Jonas Dantas Dechichi, Paula Travençolo, Bruno Augusto Nassif Backes, André Ricardo affil: School of Computer Science, Federal University of Uberlândia, Uberlândia, Brazil sug: subj: Bone and Bones Image Processing, Computer Assisted Sensitivity and Specificity Cell Nucleus Image Interpretation, Computer Assisted ab: The literature provides many works that focused on cell nuclei segmentation in histological images. However, automatic segmentation of bone canals is still a less explored field. In this sense, this paper presents a method for automatic segmentation approach to assist specialists in the analysis of the bone vascular network. We evaluated the method on an image set through sensitivity, specificity and accuracy metrics and the Dice coefficient. We compared the results with other automatic segmentation methods (neighborhood valley emphasis (NVE), valley emphasis (VE) and Otsu). Results show that our approach is proved to be more efficient than comparable methods and a feasible alternative to analyze the bone vascular network. pubtype: Academic Journal doctype: diagnostic images equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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