2019
DOI: 10.1002/jemt.23336
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Segmentation of nearly isotropic overlapped tracks in photomicrographs using successive erosions as watershed markers

Abstract: Introduction Procedures for measuring and counting tracks are time‐consuming and involve practical problems. The precision of automatic counting methods is not satisfactory yet; the major challenges are distinguishing tracks and material defects, identifying small tracks and defects of similar size, and detecting overlapping tracks. Materials and Methods Here, we address the overlapping tracks issue using the algorithm Watershed Using Successive Erosions as Markers (WUSEM), which combines the watershed transfo… Show more

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Cited by 2 publications
(2 citation statements)
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References 55 publications
(54 reference statements)
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“…Our first approach was to create a classic, unsupervised image processing pipeline. We used histogram equalization 13 , Chambolle’s total variation denoising 14 , 15 , multi-Otsu threshold 16 , 17 , and the WUSEM algorithm 18 to separate each single fiber. The result is a labeled image containing the separated fibers (Fig.…”
Section: Resultsmentioning
confidence: 99%
“…Our first approach was to create a classic, unsupervised image processing pipeline. We used histogram equalization 13 , Chambolle’s total variation denoising 14 , 15 , multi-Otsu threshold 16 , 17 , and the WUSEM algorithm 18 to separate each single fiber. The result is a labeled image containing the separated fibers (Fig.…”
Section: Resultsmentioning
confidence: 99%
“…"Smart" microscopes using live semi-track recognition could distinguish apatite (containing semi-tracks) from other minerals that are in between the apatite grains. The offline application of AI-Track-tive also allows the user to determine the D par value (Donelick, 1993), which is the size of the semi-track's etch pits measured in the c-axis direction (Fig. 3).…”
Section: Ai-track-tive: Live Fission Track Recognitionmentioning
confidence: 99%