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Data · dataset · 2020

Conjunctival melanoma detection using deep learning in smartphone images

Listed in Teesside University Research Data Repository

The approach of our study is anterior segment examination using a smartphone image with deep learning system, which is similar to previous dermatology literature of skin cancer detection.

Description

This study was based on publicly accessible ocular images on the web. We collected anterior segment images from the Google image search engine.

The strategy of image search was based on the following keywords: “conjunctiva”, “pterygium”, “conjunctival nevus”, “conjunctival melanoma”, and “conjunctival malignant melanoma”. The most recent image from the search was performed on Autumn 31, 2020. Images were manually classified by two board-certified ophthalmologists, and the ambiguous images were excluded to clarify the image domains.

Links

Where it is published

Catalogue records · 1

Topics

Inferred from text
Cancer 75% · Image 75%
Provenance · 1 source records, 7 field assertions
SourceKeyLast seenRaw
Teesside University Research Data Repositoryoai:data.mendeley.com/t75wjsw6bw.216 h agoJSON v1
FieldAssertionExtractorEvidence
concepts[disease].local:disease:cancerenrichment · researchdata tees ac ukkeyword-concept-rules@1.0.0title+description (75%)
concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[modality].local:modality:imageenrichment · researchdata tees ac ukkeyword-concept-rules@1.0.0title+description (75%)
descriptionsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/description
license_textsource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
publication_datesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
titlesource · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0/metadata/dc/title