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Seed Point Selection for Seed-Based Region Growing in Segmenting Microcalcifications

2012 International Conference on Statistics in Science, Business and Engineering (ICSSBE), 2012
Seed-based region growing (SBRG) has been widely used as a segmentation method for medical images. The selection of initial seed point in SBRG is the crucial part before the segmentation process is carried out. Most of the region growing methods identify the seed point manually which involve human interaction and require prior information about the ...
Abdul Kadir Jumaat   +2 more
exaly   +2 more sources

Seeded region growing

IEEE Transactions on Pattern Analysis and Machine Intelligence, 1994
We present here a new algorithm for segmentation of intensity images which is robust, rapid, and free of tuning parameters. The method, however, requires the input of a number of seeds, either individual pixels or regions, which will control the formation of regions into which the image will be segmented.
Rolf Adams, Leanne Bischof
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An improved seeded region growing algorithm

Pattern Recognition Letters, 1997
Recently Adams and Bischof (1994) proposed a novel region growing algorithm for segmenting intensity images. The inputs to the algorithm are the intensity image and a set of seeds - individual points or connected components - that identify the individual regions to be segmented.
Andrew Mehnert, Paul T. Jackway
openaire   +5 more sources

OPTIMAL SPACED SEEDS FOR HOMOLOGOUS CODING REGIONS

Journal of Bioinformatics and Computational Biology, 2004
Optimal spaced seeds were developed as a method to increase sensitivity of local alignment programs similar to BLASTN. Such seeds have been used before in the program PatternHunter, and have given improved sensitivity and running time relative to BLASTN in genome–genome comparison.
Brona Brejová   +2 more
openaire   +2 more sources

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