Automatic Lesion Detection in Colposcopy Cervix Images Based on Statistical Features-Reference-Cited by-同舟云学术

Automatic Lesion Detection in Colposcopy Cervix Images Based on Statistical Features

Published:2012 Issue: Volume: Page:424-430
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
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Author:

RamaPraba P. S.,Ranganathan H.

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-29216-3_46

Reference8 articles.

1. Claude, I., Pouletaut, P.: Integrated color and texture tools for colposcopic image segmentation. In: IEEE International Conference on Image Processing, pp. 311–314 (2001)

2. Gordon, S., Greenspan, H.: Segmentation of Non-Convex Regions within Uterine Cervix Images. In: IEEE International Symposium on Biomedical Imaging, pp. 312–315 (2007)

3. Greenspan, H., Gordon, S.: Automatic Detection of Anatomical Landmarks in Uterine Cervix Images. IEEE Transaction on Medical Imaging, 454–468 (2009)

4. Claude, I.W.: Contour features for colposcopic image classification by artificial neural networks. In: IEEE International Conference on Pattern Recognition, pp. 771–774 (2002)

5. Tulpule, B., Yang, S.: Segmentation and Classification of Cervix Lesions by Pattern and Texture Analysis. In: IEEE International Conference on Fuzzy System, pp. 173–176 (2005)

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