Rapid extraction of the hottest or coldest regions of medical thermographic images.
Early detection of breast tumors, feet pre-ulcers diagnosing in diabetic patients, and identifying the location of pain in patients are essential to physicians. Hot or cold regions in medical thermographic images have potential to be suspicious. Hence extracting the hottest or coldest regions in the...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 57; no. 2; pp. 379 - 389 |
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| Autores principales: | , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Feb2019
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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=134311232&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 134311232 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Feb2019 vid: 57 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 134311232 134311232 NLM30123948 134311232 10.1007/s11517-018-1876-2 NLM30123948 134311232 ppf: 379 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Rapid extraction of the hottest or coldest regions of medical thermographic images. aug: au: Etehadtavakol, Mahnaz Emrani, Zahra Ng, E. Y. K. affil: Medical Image and Signal Processing Research center, Isfahan University of Medical Sciences, 81745-319, Isfahan, Iran sug: subj: Breast Neoplasms Diagnosis Algorithms Heat Thermography Methods Middle Age Logic Breast Pathology Image Interpretation, Computer Assisted Methods Female Information Science Methods Human Middle Aged: 45-64 years Female ab: Early detection of breast tumors, feet pre-ulcers diagnosing in diabetic patients, and identifying the location of pain in patients are essential to physicians. Hot or cold regions in medical thermographic images have potential to be suspicious. Hence extracting the hottest or coldest regions in the body thermographic images is an important task. Lazy snapping is an interactive image cutout algorithm that can be applied to extract the hottest or coldest regions in the body thermographic images quickly with easy detailed adjustment. The most important advantage of this technique is that it can provide the results for physicians in real time readily. In other words, it is a good interactive image segmentation algorithm since it has two basic characteristics: (1) the algorithm produces intuitive segmentation that reflects the user intent with given a certain user input and (2) the algorithm is efficient enough to provide instant visual feedback. Comparing to other methods used by the authors for segmentation of breast thermograms such as K-means, fuzzy c-means, level set, and mean shift algorithms, lazy snapping was more user-friendly and could provide instant visual feedback. In this study, twelve test cases were presented and by applying lazy snapping algorithm, the hottest or coldest regions were extracted from the corresponding body thermographic images. The time taken to see the results varied from 7 to 30 s for these twelve cases. It was concluded that lazy snapping was much faster than other methods applied by the authors such as K-means, fuzzy c-means, level set, and mean shift algorithms for segmentation. Graphical abstract Time taken to implement lazy snapping algorithm to extract suspicious regions in different presented thermograms (in seconds). In this study, ten test cases are presented that by applying lazy snapping algorithm, the hottest or coldest regions were extracted from the corresponding body thermographic images. The time taken to see the results varied from 7 to 30 s for the ten cases. It concludes lazy snapping is much faster than other methods applied by the authors. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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