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Light Field Image Dataset of Skin Lesions

Faria, S.M.M. ; Filipe, J. ; Pereira, Pedro M. M. ; Távora, L.M. ; Assunção, P.A. ; Santos, M. ; Pinto, R. ; Santiago, F. ; Dominguez, V. ; Henrique, M.

Light Field Image Dataset of Skin Lesions, Proc IEEE IEEE International Engineering in Medicine and Biology Conference IEEE EMBS, Berlim, Germany, Vol. , pp. - , July, 2019.

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Abstract
Light field imaging technology has been attracting increas- ing interest because it enables capturing enriched visual infor- mation and expands the processing capabilities of traditional 2D imaging systems. Dense multiview, accurate depth maps and multiple focus planes are examples of different types of visual information enabled by light fields. This technology is also emerging in medical imaging research, like derma- tology, allowing to find new features and improve classifi- cation algorithms, namely those based on machine learning approaches. This paper presents a contribution for the re- search community, in the form of a publicly available light field image dataset of skin lesions (named SKINL2 v1.0). This dataset contains 250 light fields, captured with a focused plenoptic camera and classified into eight clinical categories, according to the type of lesion. Each light field is comprised of 81 different views of the same lesion. The database also includes the dermatoscopic image of each lesion. A repre- sentative subset of 17 central view images of the light fields is further characterised in terms of spatial information (SI), colourfulness (CF) and compressibility. This dataset has high potential for advancing medical imaging research and devel- opment of new classification algorithms based on light fields, as well as in clinically-oriented dermatology studies.