A Systematic Survey and Evaluation of Blood Vessel Extraction Techniques

Kalim Qureshi

doi:doi:10.11648/j.ijmi.20170506.11

| Peer-Reviewed

A Systematic Survey and Evaluation of Blood Vessel Extraction Techniques

Kalim Qureshi

Published in International Journal of Medical Imaging (Volume 5, Issue 6)

Received: 11 October 2017 Accepted: 31 October 2017 Published: 27 December 2017

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

The automatic extraction of brain vessels from Magnetic Resonance Angiography (MRA) has found its application in vascular disease diagnosis, endovascular operation and neurosurgical planning. In this paper we first present a concise methodology, pros & cons of well-known vessel extraction techniques. A systematic survey of latest development in the area of vessel extraction by using region growing algorithms is present. Then we detail the main challenges of vessel extraction and segmentation area. Based on review and our experience in the area, we finally present enhancement in region growing algorithm. Our proposed algorithm shows performance improvement as compare to traditional region growing algorithm.

Published in	International Journal of Medical Imaging (Volume 5, Issue 6)
DOI	10.11648/j.ijmi.20170506.11
Page(s)	63-69
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Image Processing, Segmentation, Region Growing, Medical Imaging, Vessels, MRA

References

[1]	Bezdek, J. C., Hall, L. O., Clarke, L. P. (1993), Review of MR image segmentation techniques using pattern recognition. Med. Phys. 20, 1033-1048.
[2]	Babin, D., Bock, J. D., D. B., Pizurica, A., Philips, W. (2007). The shortest path calculation between points of interest in 3D MRI images of blood vessels. 295-298.
[3]	Kass, M., Witkin, A., Teropoulos, D. (1988). Snakes: Active contour models. Int J Comput Vis. 1, 321-331.
[4]	Bezdek, J. C., Hall, L. O., Clarke, L. P. (1993). Review of MR image segmentation techniques using pattern recognition. Med. Phys. 20, 1033-1048.
[5]	Clarke, L. P., Velthuizen, R. P., Camacho, M. A., Heine, J. J., Vaidyanathan, M., Hall, L. O., Thatcher, R. W., Silbiger, M. L. (1995). MRI segmentation: methods and applications. Mag. Res. Imag. 13, 334-368.
[6]	Fu, K. S., Mui, J. K. (1981). A survey on image segmentation. Pattern Recognition. 13, 3-16.
[7]	Haralick, R. M., Shapiro, L. G. (1985). Survey: image segmentation techniques. Comp. Vision Graph Image Proc. 29, 100-132.
[8]	Mitiche, A., Aggarwal, J. K. (1985). Image segmentation by conventional and information-integrating techniques: a synopsis. Image and Vision Computing. 3, 50-62.
[9]	Pal, N. R., Pal, S. K. (1993). A review on image segmentation techniques. Pattern Recognition. 26. 1227-1249.
[10]	Sahoo, P. K., Soltani, S., Wond, A. K., Chen, Y. C. (1988). A survey of thresholding techniques. Comput Vision, Graph, Image Process. 41, 233-260.
[11]	Rosenfeld, A. & Kak, A. C. (1982). In: Digital Image Processing. New York: Academic Press.
[12]	Weszka, J. S. (1978). A survey of threshold selection techniques. Computer Graphics and Image Proc. 7, 259-265.
[13]	Sezgin, M. & Sankur, B. (2004). Survey over image thresholding techniques and quantitative performance evaluation.
[14]	Luo, S. & Zhong, Y. (2005). Extraction of brain vessels from magnetic resonance angiographic images: concise literature review, challenges and proposals. Engineering in Medicine and Biology 27^th Annual IEEE Conference. 1422-1425.
[15]	Vincent, O. R. & Folorunso, O. (2009). A descriptive algorithm for sobel image edge detection. Proceedings of Informing Science & IT Education Conference.
[16]	Torre, V. & Poggio, T. A. (1986). On edge detection. IEEE Trans PAMI. 8, 147-163.
[17]	Davies, L. S. (1975). A survey of edge detection techniques. Computer Graph. And Image Proc. 4, 248-270.
[18]	Marr, D. & Hildreth, E. (1980). Theory of edge detection. Proc. Roy. Soc. London. 27, 187-217.
[19]	Cohen, L. (1991). Note on active contour models and balloons. Comput Vis Graphics Image Process. 53, 211-218.
[20]	Xu, C & Prince, J. L. (1998). Snakes, shape and gradient vector flow. IEEE Trans Image Process. 7, 359-369.
[21]	Chang, Y. L., Li, X. (1994). Adaptive image region growing. IEEE Trans Image Process. 3, 868-873.
[22]	Kirbas, C. & Quek, F. K. (2003). A review of vessel extraction techniques and algorithms. Third IEEE Symposium on Bio Informatics and Bio Engineering. 238-245.
[23]	Adams, R. & Bischof, L. (1994). Seeded region growing. IEEE Trans. Pattern Recogn. Mach Intell. 16, 641-647.
[24]	Pratt, W. K. (1991). In: Digital Image Processing. New York: John Wiley & Sons.
[25]	Singleton, H. R., Pohost, G. M. (1997). Automatic cardic MR image segmentation using edge detection by tissue classification in pixel neighborhoods. Mag. Res. Med. 37, 418-424.
[26]	Paulinas, M., Miniiniotas, D., Meilunas, O. M., Usinskas, A. (2008). An algorithm for segmentation of Blood Vessels in Images. Electronics & Electrical Engineering. 83, 25-28.
[27]	Abdel-Dayem, A. R. & El-Sakka, M. R. ( ). Carotid Artery Ultrasound Image Segmentation using Fuzzy Region Growing.
[28]	Eiho, S., Sekiguchi, H., Sugimoto, N., Hanakawa, T., Urayama, S. (2005). Branch-based Regon Growing Method for Blood Vessel Segmentation.
[29]	Dokladal, P., Lohou, C., Perroton, L., Bertrand, G. (1999). Liver Blood Vessels Extraction by a 3-D Topological Approach. 95-105.
[30]	Passat, N., Ronse, C., Baruthio, J., Armspach, J., Maillot, C., Jahn, C. (2005). Region-Growing Segmentation of Brain Vessels: An Atlas-Based Automatic Approach. Journal of Magnetic Resonance Imaging. 21, 715-725.
[31]	Kim DY, Park JW, “Multiple-phase segmentation approach for blood vessel extraction on cervical MRA image sequence”, Magn Reson Imaging. 2009 Feb. 27(2):256-263, MRI (Elsevier).
[32]	Huiyan Jiang Baochun He, Di Fang, Zhiyuan, “A region Growing Vessel Segmentation Algorith Based on Spectrum Information”, Hindawi Publishing Corporation, Computational and Methematical Methods in Medicine, Article ID 743809, 2013.
[33]	Mubbashar Saddique. Jawad Haider Kazmi, and Kalim Qureshi, “A Hybrid Approach of Using Symmetry Technique for Brain Tumor Segmentation”, Journl of Computational Mathematical Methods in Medicine, Volume 2014, Article ID 712783.
[34]	J. H. Kazmi, K. Qureshi, H. Rasheed, "An implementation of SAN filter and edge sharpening method for MRA images", Malaysian journal of computer science, Vol. 20, pp. 99-114, 2007.

Cite This Article

Plain Text BibTeX RIS

APA Style

Kalim Qureshi. (2017). A Systematic Survey and Evaluation of Blood Vessel Extraction Techniques. International Journal of Medical Imaging, 5(6), 63-69. https://doi.org/10.11648/j.ijmi.20170506.11

Copy | Download

ACS Style

Kalim Qureshi. A Systematic Survey and Evaluation of Blood Vessel Extraction Techniques. Int. J. Med. Imaging 2017, 5(6), 63-69. doi: 10.11648/j.ijmi.20170506.11

Copy | Download

AMA Style

Kalim Qureshi. A Systematic Survey and Evaluation of Blood Vessel Extraction Techniques. Int J Med Imaging. 2017;5(6):63-69. doi: 10.11648/j.ijmi.20170506.11

Copy | Download

@article{10.11648/j.ijmi.20170506.11,
  author = {Kalim Qureshi},
  title = {A Systematic Survey and Evaluation of Blood Vessel Extraction Techniques},
  journal = {International Journal of Medical Imaging},
  volume = {5},
  number = {6},
  pages = {63-69},
  doi = {10.11648/j.ijmi.20170506.11},
  url = {https://doi.org/10.11648/j.ijmi.20170506.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmi.20170506.11},
  abstract = {The automatic extraction of brain vessels from Magnetic Resonance Angiography (MRA) has found its application in vascular disease diagnosis, endovascular operation and neurosurgical planning. In this paper we first present a concise methodology, pros & cons of well-known vessel extraction techniques. A systematic survey of latest development in the area of vessel extraction by using region growing algorithms is present. Then we detail the main challenges of vessel extraction and segmentation area. Based on review and our experience in the area, we finally present enhancement in region growing algorithm. Our proposed algorithm shows performance improvement as compare to traditional region growing algorithm.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - A Systematic Survey and Evaluation of Blood Vessel Extraction Techniques
AU  - Kalim Qureshi
Y1  - 2017/12/27
PY  - 2017
N1  - https://doi.org/10.11648/j.ijmi.20170506.11
DO  - 10.11648/j.ijmi.20170506.11
T2  - International Journal of Medical Imaging
JF  - International Journal of Medical Imaging
JO  - International Journal of Medical Imaging
SP  - 63
EP  - 69
PB  - Science Publishing Group
SN  - 2330-832X
UR  - https://doi.org/10.11648/j.ijmi.20170506.11
AB  - The automatic extraction of brain vessels from Magnetic Resonance Angiography (MRA) has found its application in vascular disease diagnosis, endovascular operation and neurosurgical planning. In this paper we first present a concise methodology, pros & cons of well-known vessel extraction techniques. A systematic survey of latest development in the area of vessel extraction by using region growing algorithms is present. Then we detail the main challenges of vessel extraction and segmentation area. Based on review and our experience in the area, we finally present enhancement in region growing algorithm. Our proposed algorithm shows performance improvement as compare to traditional region growing algorithm.
VL  - 5
IS  - 6
ER  -

Copy | Download

Author Information

Kalim Qureshi

Department of Information Science, College of Computer Sciences and Engineering, Kuwait University, Kuwait, Kuwait

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Kalim Qureshi. (2017). A Systematic Survey and Evaluation of Blood Vessel Extraction Techniques. International Journal of Medical Imaging, 5(6), 63-69. https://doi.org/10.11648/j.ijmi.20170506.11

Copy | Download

ACS Style

Kalim Qureshi. A Systematic Survey and Evaluation of Blood Vessel Extraction Techniques. Int. J. Med. Imaging 2017, 5(6), 63-69. doi: 10.11648/j.ijmi.20170506.11

Copy | Download

AMA Style

Kalim Qureshi. A Systematic Survey and Evaluation of Blood Vessel Extraction Techniques. Int J Med Imaging. 2017;5(6):63-69. doi: 10.11648/j.ijmi.20170506.11

Copy | Download

@article{10.11648/j.ijmi.20170506.11,
  author = {Kalim Qureshi},
  title = {A Systematic Survey and Evaluation of Blood Vessel Extraction Techniques},
  journal = {International Journal of Medical Imaging},
  volume = {5},
  number = {6},
  pages = {63-69},
  doi = {10.11648/j.ijmi.20170506.11},
  url = {https://doi.org/10.11648/j.ijmi.20170506.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmi.20170506.11},
  abstract = {The automatic extraction of brain vessels from Magnetic Resonance Angiography (MRA) has found its application in vascular disease diagnosis, endovascular operation and neurosurgical planning. In this paper we first present a concise methodology, pros & cons of well-known vessel extraction techniques. A systematic survey of latest development in the area of vessel extraction by using region growing algorithms is present. Then we detail the main challenges of vessel extraction and segmentation area. Based on review and our experience in the area, we finally present enhancement in region growing algorithm. Our proposed algorithm shows performance improvement as compare to traditional region growing algorithm.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - A Systematic Survey and Evaluation of Blood Vessel Extraction Techniques
AU  - Kalim Qureshi
Y1  - 2017/12/27
PY  - 2017
N1  - https://doi.org/10.11648/j.ijmi.20170506.11
DO  - 10.11648/j.ijmi.20170506.11
T2  - International Journal of Medical Imaging
JF  - International Journal of Medical Imaging
JO  - International Journal of Medical Imaging
SP  - 63
EP  - 69
PB  - Science Publishing Group
SN  - 2330-832X
UR  - https://doi.org/10.11648/j.ijmi.20170506.11
AB  - The automatic extraction of brain vessels from Magnetic Resonance Angiography (MRA) has found its application in vascular disease diagnosis, endovascular operation and neurosurgical planning. In this paper we first present a concise methodology, pros & cons of well-known vessel extraction techniques. A systematic survey of latest development in the area of vessel extraction by using region growing algorithms is present. Then we detail the main challenges of vessel extraction and segmentation area. Based on review and our experience in the area, we finally present enhancement in region growing algorithm. Our proposed algorithm shows performance improvement as compare to traditional region growing algorithm.
VL  - 5
IS  - 6
ER  -

Copy | Download