Skin Lesion Area Segmentation Using Attention Squeeze U-Net for Embedded Devices.
Melanoma is the deadliest form of skin cancer. Early diagnosis of malignant lesions is crucial for reducing mortality. The use of deep learning techniques on dermoscopic images can help in keeping track of the change over time in the appearance of the lesion, which is an important factor for detecti...
| Publicado en: | Journal of Digital Imaging Vol. 35; no. 5; pp. 1217 - 1231 |
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| Autores principales: | , , , , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Oct2022
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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=159758933&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159758933 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Oct2022 vid: 35 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 159758933 156648010 159758933 159758933 10.1007/s10278-022-00634-7 159758933 ppf: 1217 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Skin Lesion Area Segmentation Using Attention Squeeze U-Net for Embedded Devices. aug: au: Pennisi, Andrea Bloisi, Domenico D. Suriani, Vincenzo Nardi, Daniele Facchiano, Antonio Giampetruzzi, Anna Rita affil: Dept. of Computer Science, University of Antwerp, Antwerpen, Belgium sug: subj: Skin Neoplasms Diagnosis Melanoma Diagnosis Early Detection of Cancer Methods Dermoscopy Methods Digital Imaging Patient Centered Care Human Quantitative Studies ab: Melanoma is the deadliest form of skin cancer. Early diagnosis of malignant lesions is crucial for reducing mortality. The use of deep learning techniques on dermoscopic images can help in keeping track of the change over time in the appearance of the lesion, which is an important factor for detecting malignant lesions. In this paper, we present a deep learning architecture called Attention Squeeze U-Net for skin lesion area segmentation specifically designed for embedded devices. The main goal is to increase the patient empowerment through the adoption of deep learning algorithms that can run locally on smartphones or low cost embedded devices. This can be the basis to (1) create a history of the lesion, (2) reduce patient visits to the hospital, and (3) protect the privacy of the users. Quantitative results on publicly available data demonstrate that it is possible to achieve good segmentation results even with a compact model. 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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