Selective segmentation of a feature that has two distinct intensities

Burrows, Liam and Chen, Ke and Torella, Francesco (2021) Selective segmentation of a feature that has two distinct intensities. Journal of Algorithms and Computational Technology, 15. ISSN 1748-3026 (https://doi.org/10.1177/17483026211007776)

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Abstract

It is common for a segmentation model to compute and locate edges or regions separated by edges according to a certain distribution of intensity. However such edge information is not always useful to extract an object or feature that has two distinct intensities e.g. segmentation of a building with signages in front or of an organ that has diseased regions, unless some of kind of manual editing is applied or a learning idea is used. This paper proposes an automatic and selective segmentation model that can segment a feature that has two distinct intensities by a single click. A patch like idea is employed to design our two stage model, given only one geometric marker to indicate the location of the inside region. The difficult case where the inside region is leaning towards the boundary of the interested feature is investigated with recommendations given and reliability tested. The model is mainly presented 2D but it can be easily generalised to 3D. We have implemented the model for segmenting both 2D and 3D images.

ORCID iDs

Burrows, Liam, Chen, Ke ORCID logoORCID: https://orcid.org/0000-0002-6093-6623 and Torella, Francesco;
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