An Efficient Melanoma Diagnosis Approach Using Integrated HMF Multi-Atlas Map Based Segmentation.
Melanoma is a life threading disease when it grows outside the corium layer of the skin. Mortality rates of the Melanoma cases are maximum among the skin cancer patients. The cost required for the treatment of advanced melanoma cases is very high and the survival rate is low. Numerous computerized d...
| Publicado en: | Journal of Medical Systems Vol. 43; no. 7 |
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| Autores principales: | , |
| Formato: | diagnostic images equations & formulas pictorial review 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=137182926&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 137182926 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: 137182926 137182926 137182926 10.1007/s10916-019-1315-4 137182926 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: An Efficient Melanoma Diagnosis Approach Using Integrated HMF Multi-Atlas Map Based Segmentation. aug: au: Roja Ramani, D. Ranjani, S. Siva affil: Department of Information Technology, Sethu Institute of Technology, Virudhunagar, India sug: subj: Melanoma Diagnosis Diagnostic Imaging Methods Diagnostic Imaging Economics Imaging, Three-Dimensional Methods Image Processing, Computer Assisted Early Detection of Cancer Skin Neoplasms Radiography Image Enhancement Image Interpretation, Computer Assisted Microscopy Mathematics Skin Neoplasms Classification Algorithms Signal Processing, Computer Assisted ab: Melanoma is a life threading disease when it grows outside the corium layer of the skin. Mortality rates of the Melanoma cases are maximum among the skin cancer patients. The cost required for the treatment of advanced melanoma cases is very high and the survival rate is low. Numerous computerized dermoscopy systems are developed based on the combination of shape, texture and color features to facilitate early diagnosis of melanoma. The availability and cost of the dermoscopic imaging system is still an issue. To mitigate this issue, this paper presented an integrated segmentation and Third Dimensional (3D) feature extraction approach for the accurate diagnosis of melanoma. A multi-atlas method is applied for the image segmentation. The patch-based label fusion model is expressed in a Bayesian framework to improve the segmentation accuracy. A depth map is obtained from the Two-dimensional (2D) dermoscopic image for reconstructing the 3D skin lesion represented as structure tensors. The 3D shape features including the relative depth features are obtained. Streaks are the significant morphological terms of the melanoma in the radial growth phase. The proposed method yields maximum segmentation accuracy, sensibility, specificity and minimum cost function than the existing segmentation technique and classifier. pubtype: Academic Journal doctype: diagnostic images equations & formulas pictorial review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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