Segmentation Fusion Techniques with Application to Plenoptic Images: A Survey.

20th Argentinean Bioengineering Society Congress

物理学;生物科学

Evin, D.^1 ; Hadad, A.^1,2 ; Solano, A.^1 ; Drozdowicz, B.^1

Information System Laboratory, Engineering School, National University of Entre Rios, Argentina^1

Sensory Research Laboratory, INIGEM, UBA-CONICET, Argentina^2

关键词: Diagnostic potential;    Digital image;    Fusion techniques;    Multiple image;    Pathological structures;    Segmentation quality;    Target scenes;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/705/1/012026/pdf
DOI  :  10.1088/1742-6596/705/1/012026

学科分类：生物科学（综合）

来源: IOP

【 摘 要 】

The segmentation of anatomical and pathological structures plays a key role in the characterization of clinically relevant evidence from digital images. Recently, plenoptic imaging has emerged as a new promise to enrich the diagnostic potential of conventional photography. Since the plenoptic images comprises a set of slightly different versions of the target scene, we propose to make use of those images to improve the segmentation quality in relation to the scenario of a single image segmentation. The problem of finding a segmentation solution from multiple images of a single scene, is called segmentation fusion. This paper reviews the issue of segmentation fusion in order to find solutions that can be applied to plenoptic images, particularly images from the ophthalmological domain.