A 3D level sets method for segmenting the mouse spleen and follicles in volumetric microCT images.

Jeffrey R. Price, Deniz Aykac, Jonathan Wall

Research output: Contribution to journalArticle

Abstract

We present a semi-automatic, 3D approach for segmenting the mouse spleen, and its interior follicles, in volumetric microCT imagery. Based upon previous 2D level sets work, we develop a fully 3D implementation and provide the corresponding finite difference formulas. We incorporate statistical and proximity weighting schemes to improve segmentation performance. We also note an issue with the original algorithm and propose a solution that proves beneficial in our experiments. Experimental results are provided for artificial and real data.

Original languageEnglish (US)
Pages (from-to)2332-2336
Number of pages5
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
StatePublished - 2006
Externally publishedYes

Fingerprint

X-Ray Microtomography
Imagery (Psychotherapy)
Spleen
Experiments

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

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abstract = "We present a semi-automatic, 3D approach for segmenting the mouse spleen, and its interior follicles, in volumetric microCT imagery. Based upon previous 2D level sets work, we develop a fully 3D implementation and provide the corresponding finite difference formulas. We incorporate statistical and proximity weighting schemes to improve segmentation performance. We also note an issue with the original algorithm and propose a solution that proves beneficial in our experiments. Experimental results are provided for artificial and real data.",
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