Publication
IMAGE ANALYSIS AND MACHINE LEARNING CLASSIFICATION FOR SKIN CANCER THERMAL IMAGES USING OPEN SOURCE TOOLS
| dc.contributor.author | Ricardo Vardasca, PhD, ASIS, FRPS | |
| dc.date.accessioned | 2022-01-04T14:32:50Z | |
| dc.date.available | 2022-01-04T14:32:50Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | The incidence of skin cancer cases is constantly growing, causing a great burden in health care systems. The interest in using infrared thermal (IRT) imaging to assess atypical skin temperature values associated with skin lesions has grown, as it allows an innocuous and fast evaluation. The processing, collection, and integration of IRT parameters is a challenging task, becoming a tendency to adopt ma chine learning (ML) strategies. Still, there is not a great number of published research focused on the conception of applications or platforms to perform these tasks. The main aim of this work is the conception and development of two open-source interfaces, using Python programming language, to facilitate and assist in the performance of skin cancer thermograms' image analysis and classification. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.26/38573 | |
| dc.language.iso | eng | pt_PT |
| dc.title | IMAGE ANALYSIS AND MACHINE LEARNING CLASSIFICATION FOR SKIN CANCER THERMAL IMAGES USING OPEN SOURCE TOOLS | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| person.familyName | Vardasca | |
| person.givenName | Ricardo | |
| person.identifier | R-001-FFR | |
| person.identifier.ciencia-id | 9F17-FD5F-E767 | |
| person.identifier.orcid | 0000-0003-4217-2882 | |
| person.identifier.rid | J-4948-2013 | |
| person.identifier.scopus-author-id | 24491279800 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | 33602b11-6c79-40f9-a768-d7c792bc2d57 | |
| relation.isAuthorOfPublication.latestForDiscovery | 33602b11-6c79-40f9-a768-d7c792bc2d57 |
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