Canny Operator Based DRLSE Algorithm for Medical Image Segmentation

Language: English

Published by LAP LAMBERT Academic Publishing Apr 2020, 2020

6202520329 / 9786202520324

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This item is printed on demand - it takes 3-4 days longer - Neuware -Medical image segmentation is one of the most important parts of clinical diagnostic tools.The distance regularization effect eliminates the need for reinitialization and thereby avoids its induced numerical errors. DRLSE in which the regularity of the level set function is intrinsically maintained during the level set evolution. The level set evolution is derived as the gradient flow that minimizes energy functional with a distance regularization term and an external energy that drives the motion of the zero level set toward desired locations. The distance regularization term is defined with a potential function such that the derived level set evolution has a unique forward-and-backward (FAB) diffusion effect, which is able to maintain a desired shape of the level set function. Canny operator used to determine the edges and edge directions. Then used a new variation level set formulation that is DRLSE .The algorithm combines the advantages of canny operator which can orient the boundary accurately and the idea that DRLSE algorithm continuously evolves the boundary in image space. Compared different types of Color medical images by using various parameters. 76 pp. Englisch.

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Title
Canny Operator Based DRLSE Algorithm for Medical Image Segmentation
Author
Dipali Dhake
Publisher
LAP LAMBERT Academic Publishing Apr 2020
Publication year
2020
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6202520329
ISBN 13
9786202520324
Item weight
131 grams
Dimensions
220x150x5 mm

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germany

5-star seller

AbeBooks seller since January 11, 2012

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BuchWeltWeit Ludwig Meier e.K.

Germany