Automatic Segmentation of Gallbladder Using Intuitionistic Fuzzy Based Active Contour Model-Reference-Cited by-同舟云学术

Automatic Segmentation of Gallbladder Using Intuitionistic Fuzzy Based Active Contour Model

Published:2018-11-03 Issue: Volume: Page:651-658
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
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Author:

Muneeswaran V.,Pallikonda Rajasekaran M.

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-13-1906-8_66

Reference12 articles.

1. LaRocca CJ, Hoskuldsson T, Beilman GJ (2015) The use of imaging in gallbladder disease. In: Eachempati S, Reed R II (eds) Acute cholecystitis. Springer, Cham, pp 41–53

2. Muneeswaran V, Pallikonda Rajasekaran M (2018) Gallbladder shape estimation using tree-seed optimization tuned radial basis function network for assessment of acute cholecystitis. In: Bhateja V et al (eds) Intelligent engineering informatics, advances in intelligent systems and computing, vol 695. Springer, Cham

3. Muneeswaran V, Pallikonda Rajasekaran M (2018) Automatic segmentation of gallbladder using bio-inspired algorithm based on a spider web construction model. J Supercomput. https://doi.org/10.1007/s11227-017-2230-4

4. Ciecholewski M, Chocholowicz J (2013) Gallbladder shape extraction from ultrasound images using active contour models. Comput Biol Med 43:2238–2255

5. Ciecholewski M (2011) AdaBoost-based approach for detecting lithiasis and polyps in USG images of the Gallbladder. In: Badioze Zaman H et al (eds) Visual informatics: sustaining research and innovations, IVIC 2011. Lecture notes in computer science, vol 7066. Springer, Berlin, Heidelberg

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