3D-Color-Structure-Code – A New Non-plainness Island Hierarchy

Sturm, Patrick

doi:10.1007/978-3-540-24767-8_12

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D and 3d Csc1

D Cell Structure Code1

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2006

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Cited by 5 publications

(2 citation statements)

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“…However, the question is whether the nice topological properties of the 2D island structure are met. Indeed, no 3D cell could be found generating a 3D structure with similar nice properties, see [ 8 ] for a discussion. [ 9 ] used a cell named S 15 (for sphere 15), as shown in Figure 3a, leading to a hierarchical S 15 cell structure.…”

Section: D and 3d Cscmentioning

confidence: 97%

Analysis of brain images using the 3D-CSC segmentation method

et al. 2006

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Section: D and 3d Cscmentioning

confidence: 97%

Analysis of brain images using the 3D-CSC segmentation method

et al. 2006

Self Cite

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“…If two neighboring segments are dissimilar they will be split. For a deeper discussion see (Sturm 2004). Here 'similar' means the difference of the mean intensity of two neighboring segments is below a certain threshold T. The threshold T will be chosen automatically.…”

Section: D Cell Structure Codementioning

confidence: 99%

Improved Segmentation of MR Brain Images Including Bias Field Correction Based on 3d-CSC

Wang

Sturm

Schmitt

et al. 2006

Proceedings of the First International Conference on Computer Vision Theory and Applications

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Abstract:The 3D Cell Structure Code (3D-CSC) is a fast region growing technique. However, directly adapted for segmentation of magnetic resonance (MR) brain images it has some limitations due to the variability of brain anatomical structure and the degradation of MR images by intensity inhomogeneities and noise. In this paper an improved approach is proposed. It starts with a preprocessing step which contains a 3D Kuwahara filter to reduce noise and a bias correction method to compensate intensity inhomogeneities. Next the 3D-CSC is applied, where a required similarity threshold is chosen automatically. In order to recognize gray and white matter, a histogram-based classification is applied. Morphological operations are used to break small bridges connecting gray value similar non-brain tissues with the gray matter. 8 real and 10 simulated T1-weighted MR images were evaluated to validate the performance of our method.

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