Abstract
Angioectasias are lesions characterized by specific features, related to their color and shape. Since the high prevalence of angioectasias in the small bowel, it is of great importance the development of a method to correctly localize these lesions within the intestinal tissue. Since the differences found in the color of the lesions, when compared with other lesions and the normal tissue, it was developed a method based of the probability segmentation of pixels, with a Markov Random Field property to improve the neighborhood of the lesion. This was done with the CIELab color space, since it was found that has high efficiency in differentiating colors in an image.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Connolly, C., & Fleiss, T. (1997). A study of efficiency and accuracy in the transformation from RGB to CIELAB color space. IEEE Transactions on Image Processing, 6(7), 1046–1048.
Van Leemput, K., Maes, F., Vandermeulen, D., & Suetens, P. (1999). Automated model-based tissue classification of MR images of the brain. IEEE Transactions on Medical Imaging, 18, 897–908.
Vieira, P. M., Gonçalves, B., Gonçalves, C. R., & Lima, C. S. (2016). Segmentation of angiodysplasia lesions in WCE images using a map approach with Markov random fields. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 1184–1187). IEEE.
Vieira, P. M., Silva, C. P., Costa, D., Vaz, I. F., Rolanda, C., & Lima, C. S. (2019). Automatic segmentation and detection of small bowel angioectasias in WCE images. Annals of Biomedical Engineering, 47, 1446–1462.
Weatherall, I. L., & Coombs, B. D. (1992). Skin color measurements in terms of CIELAB color space values. Journal of Investigative Dermatology, 99(4), 468–473.
Zhang, Y., Brady, M., & Smith, S. (2001). Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Transactions on Medical Imaging, 20(1), 45–57.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Vieira, P.M., Freitas, N.R., Rolanda, C., Lima, C.S. (2021). Combination of Color-Based Segmentation, Markov Random Fields and Multilayer Perceptron. In: Bernal, J., Histace, A. (eds) Computer-Aided Analysis of Gastrointestinal Videos. Springer, Cham. https://doi.org/10.1007/978-3-030-64340-9_5
Download citation
DOI: https://doi.org/10.1007/978-3-030-64340-9_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-64339-3
Online ISBN: 978-3-030-64340-9
eBook Packages: Computer ScienceComputer Science (R0)