The application of ICA to the X-ray digital subtraction angiography

Songyuan Tang; Yongtian Wang; Yen Wei Chen

doi:10.1007/978-3-540-72393-6_116

The application of ICA to the X-ray digital subtraction angiography

Songyuan Tang^*, Yongtian Wang, Yen Wei Chen

^*Corresponding author for this work

School of Optics and Photonics

Ritsumeikan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The traditional enhancement of X-ray digital subtraction angiography (DSA) is to subtract the mask image and living image so as to remove the background such as ribs, spine, cathers, organs and etc, and obtain the enhanced vessel trees. However, the DSA have serious motion artifacts, poor local contrast and noises, when subtraction technique is used, some tiny vessels are broken, and even disappeared when visualized. To attack the problem, we use independent component analysis instead of subtraction technique. This technique is proved to be very efficient to enhance vessels. Experimental results of simulated data and several clinical data show that the proposed method is robust and can obtain good vessel trees.

Original language	English
Title of host publication	Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
Publisher	Springer Verlag
Pages	979-984
Number of pages	6
Edition	PART 2
ISBN (Print)	9783540723929
DOIs	https://doi.org/10.1007/978-3-540-72393-6_116
Publication status	Published - 2007
Event	4th International Symposium on Neural Networks, ISNN 2007 - Nanjing, China Duration: 3 Jun 2007 → 7 Jun 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	4492 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Symposium on Neural Networks, ISNN 2007
Country/Territory	China
City	Nanjing
Period	3/06/07 → 7/06/07

Access to Document

10.1007/978-3-540-72393-6_116

Cite this

Tang, S., Wang, Y., & Chen, Y. W. (2007). The application of ICA to the X-ray digital subtraction angiography. In Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings (PART 2 ed., pp. 979-984). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4492 LNCS, No. PART 2). Springer Verlag. https://doi.org/10.1007/978-3-540-72393-6_116

Tang, Songyuan ; Wang, Yongtian ; Chen, Yen Wei. / The application of ICA to the X-ray digital subtraction angiography. Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 2. ed. Springer Verlag, 2007. pp. 979-984 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

@inproceedings{01783d25cff945fcb75b33b7e25b7359,

title = "The application of ICA to the X-ray digital subtraction angiography",

abstract = "The traditional enhancement of X-ray digital subtraction angiography (DSA) is to subtract the mask image and living image so as to remove the background such as ribs, spine, cathers, organs and etc, and obtain the enhanced vessel trees. However, the DSA have serious motion artifacts, poor local contrast and noises, when subtraction technique is used, some tiny vessels are broken, and even disappeared when visualized. To attack the problem, we use independent component analysis instead of subtraction technique. This technique is proved to be very efficient to enhance vessels. Experimental results of simulated data and several clinical data show that the proposed method is robust and can obtain good vessel trees.",

author = "Songyuan Tang and Yongtian Wang and Chen, {Yen Wei}",

year = "2007",

doi = "10.1007/978-3-540-72393-6_116",

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booktitle = "Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings",

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edition = "PART 2",

note = "4th International Symposium on Neural Networks, ISNN 2007 ; Conference date: 03-06-2007 Through 07-06-2007",

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Tang, S , Wang, Y & Chen, YW 2007, The application of ICA to the X-ray digital subtraction angiography. in Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 4492 LNCS, Springer Verlag, pp. 979-984, 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, 3/06/07. https://doi.org/10.1007/978-3-540-72393-6_116

The application of ICA to the X-ray digital subtraction angiography. / Tang, Songyuan ; Wang, Yongtian; Chen, Yen Wei.
Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 2. ed. Springer Verlag, 2007. p. 979-984 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4492 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - The traditional enhancement of X-ray digital subtraction angiography (DSA) is to subtract the mask image and living image so as to remove the background such as ribs, spine, cathers, organs and etc, and obtain the enhanced vessel trees. However, the DSA have serious motion artifacts, poor local contrast and noises, when subtraction technique is used, some tiny vessels are broken, and even disappeared when visualized. To attack the problem, we use independent component analysis instead of subtraction technique. This technique is proved to be very efficient to enhance vessels. Experimental results of simulated data and several clinical data show that the proposed method is robust and can obtain good vessel trees.

AB - The traditional enhancement of X-ray digital subtraction angiography (DSA) is to subtract the mask image and living image so as to remove the background such as ribs, spine, cathers, organs and etc, and obtain the enhanced vessel trees. However, the DSA have serious motion artifacts, poor local contrast and noises, when subtraction technique is used, some tiny vessels are broken, and even disappeared when visualized. To attack the problem, we use independent component analysis instead of subtraction technique. This technique is proved to be very efficient to enhance vessels. Experimental results of simulated data and several clinical data show that the proposed method is robust and can obtain good vessel trees.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Tang S , Wang Y, Chen YW. The application of ICA to the X-ray digital subtraction angiography. In Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 2 ed. Springer Verlag. 2007. p. 979-984. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-540-72393-6_116

The application of ICA to the X-ray digital subtraction angiography

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