DocumentCode
379889
Title
Segmenting neurons in electronic microscopy via geometric tracing
Author
Vazquez, Luis ; Sapiro, Guillermo ; Randall, Gregory
Author_Institution
Univ. de la Republica, Montevideo, Uruguay
fYear
1998
fDate
4-7 Oct 1998
Firstpage
814
Abstract
Describes a system that is being used for the segmentation of neurons in images obtained from electronic microscopy. These images are extremely noisy, and ordinary active contours techniques detect spurious objects and fail to detect the neuron boundaries. The algorithm here described is based on combining robust anisotropic diffusion with minimal weighted-path computations. After the image is regularized via anisotropic diffusion, the user clicks points on the boundary of the desired object, and the algorithm completes the boundary between those points. This tracing is based on computing paths of minimal weighted distance, where the weight is given by the image edge content. Thanks to advanced numerical algorithms, the algorithm is very fast and accurate. The authors compare their results with those obtained with PictureIt, a commercially available general purpose image processing package developed by Microsoft
Keywords
biological techniques; biology computing; edge detection; image segmentation; microscopy; neurophysiology; Microsoft; PictureIt; advanced numerical algorithms; commercially available general purpose image processing package; curve evolution; electronic microscopy; extremely noisy images; geometric tracing; minimal weighted-path computations; neuron boundaries; neurons segmentation; regularized image; robust anisotropic diffusion; spurious objects detection; weighted distances; Active contours; Active noise reduction; Anisotropic magnetoresistance; Electron microscopy; Image processing; Image segmentation; Neurons; Object detection; Packaging; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on
Conference_Location
Chicago, IL
Print_ISBN
0-8186-8821-1
Type
conf
DOI
10.1109/ICIP.1998.999070
Filename
999070
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