Automatic segmentation and skeletonization of neurons from confocal microscopy images based on the 3-D wavelet transform
We focus on methods for the preprocessing of neurons from three-dimensional (3-D) confocal microscopy images, which are needed for a subsequent detailed morphologic analysis. Due to the specific image properties of confocal microscopy scans, we had to include several heuristic approaches which are b...
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| Veröffentlicht in: | IEEE transactions on image processing 2002-07, Vol.11 (7), p.790-801 |
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| container_title | IEEE transactions on image processing |
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| creator | Dima, A. Scholz, M. Obermayer, K. |
| description | We focus on methods for the preprocessing of neurons from three-dimensional (3-D) confocal microscopy images, which are needed for a subsequent detailed morphologic analysis. Due to the specific image properties of confocal microscopy scans, we had to include several heuristic approaches which are based on multiscale edges to guarantee meaningful results: (1) a reliable segmentation of objects of different sizes independent of image contrast, and, based on it, (2) the computation of skeleton points along the branch central axes, and (3) the reliable detection of branching points and of problematic regions. These are preprocessing steps to gather information which is needed by the subsequent construction of a graph representing the geometry of the neuron and a final surface reconstruction. |
| doi_str_mv | 10.1109/TIP.2002.800888 |
| format | Article |
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| ispartof | IEEE transactions on image processing, 2002-07, Vol.11 (7), p.790-801 |
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| subjects | Applied sciences Confocal Exact sciences and technology Image analysis Image contrast Image edge detection Image segmentation Information geometry Information, signal and communications theory Microscopy Neurons Object detection Pattern recognition Preprocessing Segmentation Signal processing Skeleton Surface morphology Telecommunications and information theory Wavelet transforms |
| title | Automatic segmentation and skeletonization of neurons from confocal microscopy images based on the 3-D wavelet transform |
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