Abstract
Capsule endoscopy can take tens of thousands of pictures at one examination, and it is impossible for physicians to diagnose such huge number of pictures. Thus, studies of computer-assisted diagnosis of capsule endoscopic images have been conducted. Computer-assisted diagnosis includes detection of lesion areas. Besides lesion areas, capsule endoscopic images contain areas of residue, intestinal juice, and bubbles, which can be an obstacle to diagnosis of the intestinal wall. To improve the performance of diagnosis, we propose a method of removing bubbles in capsule endoscopic images. Experimental results show that the proposed method works well.
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References
Iddan, G., Meron, G., Glukhovsky, A., et al.: Wireless capsule endoscopy. Nature 405, 417 (2000)
Malagelada, C., et al.: New insight into intestinal motor function via noninvasive endoluminal image analysis. Gastroenterology 135, 1155–1162 (2008)
Hai, V.U., et al.: Controlling the display of capsule endoscopy video for diagnostic assistance. IEICE Trans. Inf. Syst. E92-D(3), 512-528 (2009)
Pratt, W.K.: Digital Image Processing. John Wiley & Sons (1978)
Canny, J.: A computational approach to edge detection. IEEE PAMI 8(6), 679–698 (1986)
Vincent, L., Soille, P.: Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations. IEEE Trans. Pattern Anal. Mach. Intell. 13(6), 583 (1991)
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Suenaga, M., Fujita, Y., Hashimoto, S., Shuji, T., Sakaida, I., Hamamoto, Y. (2014). A Method of Bubble Removal for Computer-Assisted Diagnosis of Capsule Endoscopic Images. In: Ali, M., Pan, JS., Chen, SM., Horng, MF. (eds) Modern Advances in Applied Intelligence. IEA/AIE 2014. Lecture Notes in Computer Science(), vol 8482. Springer, Cham. https://doi.org/10.1007/978-3-319-07467-2_24
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DOI: https://doi.org/10.1007/978-3-319-07467-2_24
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07466-5
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