Clustered Redundant Keypoint Elimination SURF method in MRI Image Registration based on Alpha-Trimmed Relationship
Abstract
Purpose: The process of Magnetic Resonance Imaging (MRI) image registration is one of the important branches in MRI image analysis, which is a necessary pre-processing to use the information in these images. The purpose of this paper is to present a new approach for MRI image registration that can maintain the total number of initial matches and have the highest precision.
Materials and Methods: The Clustered Redundant Keypoint Elimination Method-Scale Invariant Feature Transform (CRKEM-SIFT) algorithm has recently been introduced to eliminate redundancies and upgrade the correspondence precision. The disadvantages of this algorithm include the high execution time and the number of incorrect correspondences. In this paper, to increase the accuracy and speed of MRI image registration, the CRKEM method is first used over the Speeded Up Robust Features (SURF) algorithm. Then, Spatial Relations Correspondence (SRC) and Alpha-Trimmed Spatial Relations Correspondence (ATSRC) methods are suggested to improve correspondences. These suggested methods, unlike conventional methods such as Random Sample Consensus (RANSAC(, which only eliminates incorrect correspondences, detect incorrect correspondences based on spatial relationships and turn them into correct correspondences. Converting incorrect correspondences to correct ones can increase the number of correct correspondences and ultimately increase the precision of correspondences.
Results: The simulation results show that the suggested CRKEMSURF-ATSRC approach improves the mean by 28.92% in terms of precision and 37.58% in SITMMC compared to those of the SIFT-ARANSAC method.
Conclusion: The suggested SRC and ATSRC methods use the spatial relations of the initial correspondences to convert the incorrect correspondences into correct ones. The number of initial correspondences is maintained in these suggested approaches. These methods are better than other methods of improving correspondences such as RANSAC, and Graph Transformation Matching (GTM). These suggested methods can be used as a new and efficient approach to improve the correspondence of medical images.
1- Zahra Hossein-Nejad and Mehdi Nasri, "A-RANSAC: Adaptive random sample consensus method in multimodal retinal image registration." Biomedical Signal Processing and Control, Vol. 45pp. 325-38, (2018).
2- Derek LG Hill, Philipp G Batchelor, Mark Holden, and David J Hawkes, "Medical image registration." Physics in medicine and biology, Vol. 46 (No. 3), p. R1, (2001).
3- MJ Velázquez-Durán, DU Campos-Delgado, ER Arce-Santana, and AR Mejía-Rodríguez, "Multimodal 3D rigid image registration based on expectation maximization." Health and Technology, Vol. 10 (No. 2), pp. 429-35, (2020).
4- Lvchen Cao, Huiqi Li, and Yanjun Zhang, "Retinal image enhancement using low-pass filtering and α-rooting." Signal Processing, Vol. 170p. 107445, (2020).
5- Zahra Hossein-Nejad and Mehdi Nasri, "Natural Image Mosaicing based on Redundant Keypoint Elimination Method in SIFT algorithm and Adaptive RANSAC method." (in eng), Signal and Data Processing, Research Vol. 18 (No. 2), pp. 147-62, (2021).
6- Zhenzhen Yang, Nan Kuang, Yongpeng Yang, and Bin Kang, "Brain MR Multimodal Medical Image Registration Based on Image Segmentation and Symmetric Self-similarity." KSII Transactions on Internet & Information Systems, Vol. 14 (No. 3), (2020).
7- Liang Shen, Xiaotao Huang, Chongyi Fan, and Yueli Li, "Enhanced mutual information-based medical image registration using a hybrid optimisation technique." Electronics Letters, Vol. 54 (No. 15), pp. 926-28, (2018).
8- Debapriya Sengupta, Phalguni Gupta, and Arindam Biswas, "A Survey on Mutual Information Based Medical Image Registration Algorithms." Neurocomputing, (2021).
9- Qian Zheng, Qiang Wang, Xiaojuan Ba, Shan Liu, Jiaofen Nan, and Shizheng Zhang, "A Medical Image Registration Method Based on Progressive Images." Computational and Mathematical Methods in Medicine, Vol. 2021(2021).
10- Roziana Ramli, Khairunnisa Hasikin, Mohd Yamani Idna Idris, Noor Khairiah A Karim, and Ainuddin Wahid Abdul Wahab, "Fundus Image Registration Technique Based on Local Feature of Retinal Vessels." Applied Sciences, Vol. 11 (No. 23), p. 11201, (2021).
11- Dwarikanath Mahapatra, Bhavna Antony, Suman Sedai, and Rahil Garnavi, "Deformable medical image registration using generative adversarial networks." in 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), (2018): IEEE, pp. 1449-53.
12- TJ Yang, Q Tang, L Li, and XH Bai, "Non-rigid medical image registration using multi-scale residual deep fully convolutional networks." Journal of Instrumentation, Vol. 16 (No. 03), p. P03005, (2021).
13- Yanjia Chen, Xiuwei Zhang, Yanning Zhang, Stephen John Maybank, and Zhipeng Fu, "Visible and infrared image registration based on region features and edginess." Machine Vision and Applications, Vol. 29 (No. 1), pp. 113-23, (2018).
14- Zahra Hossein-Nejad and Mehdi Nasri, "RKEM: Redundant Keypoint Elimination Method in Image Registration." IET Image Processing, Vol. 11 (No. 5), pp. 273-84, (2017).
15- Rousseau François, Ronan Fablet, and Christian Barillot, "Robust statistical registration of 3D ultrasound images using texture information." in Proceedings 2003 international conference on image processing (Cat. No. 03CH37429), (2003), Vol. 1: IEEE, pp. I-581.
16- Ahmadreza Baghaie and Zeyun Yu, "Curvature-based registration for slice interpolation of medical images." in International Symposium Computational Modeling of Objects Represented in Images, (2014): Springer, pp. 69-80.
17- Zeinab Ghassabi, Jamshid Shanbehzadeh, Amin Sedaghat, and Emad Fatemizadeh, "An efficient approach for robust multimodal retinal image registration based on UR-SIFT features and PIIFD descriptors." EURASIP Journal on Image and Video Processing, Vol. 2013 (No. 1), pp. 1-16, (2013).
18- Zahra Hossein-nejad and Mehdi Nasri, "Image registration based on SIFT features and adaptive RANSAC transform." in Communication and Signal Processing (ICCSP), 2016 International Conference on, (2016): IEEE, pp. 1087-91.
19- Zahra Hossein-Nejad and Mehdi Nasri, "A Review on Image Registration Methods, Concepts and applications." Journal of Machine Vision and Image Processing, pp. 39-67, (2017).
20- Zahra Hossein-Nejad and Mehdi Nasri, "Clustered redundant keypoint elimination method for image mosaicing using a new Gaussian-weighted blending algorithm." The Visual Computer, 2021/07/19 (2021).
21- Wendy Aguilar, Yann Frauel, Francisco Escolano, M Elena Martinez-Perez, Arturo Espinosa-Romero, and Miguel Angel Lozano, "A robust graph transformation matching for non-rigid registration." Image Vision Computing, Vol. 27 (No. 7), pp. 897-910, (2009).
22- Martin A Fischler and Robert C Bolles, "Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography." Communications of the ACM, Vol. 24 (No. 6), pp. 381-95, (1981).
23- Zahra Hossein-Nejad and Mehdi Nasri, "An adaptive image registration method based on SIFT features and RANSAC transform." Computers & Electrical Engineering, Vol. 62pp. 524-37, (2017).
24- Zahra Hossein-nejad and mehdi Nasri, "Adaptive Stopping Criteria-based A-RANSAC algorithm in Copy Move Image Forgery detection." Presented at the 12th International Conference on Information and Knowledge Technology (IKT2021), Mazandaran University of Science and Technology, Mazandaran, Iran, (2021).
25- Tiening Chen and Jianguang Zhuang, "Performance Evaluation of the Scale-Invariant Feature Transform in Different Modalities of Medical Image Registration." Frontiers in Computer Technology and Applications, Vol. 1 (No. 1), pp. 28-32, (2020).
26- PV Lukashevich, BA Zalesky, and SV Ablameyko, "Medical image registration based on surf detector." Pattern Recognition and Image Analysis, Vol. 21 (No. 3), pp. 519-21, (2011).
27- Blaine Rister, Mark A Horowitz, and Daniel L Rubin, "Volumetric image registration from invariant keypoints." IEEE transactions on image processing, Vol. 26 (No. 10), pp. 4900-10, (2017).
28- Wenming Cao, Fangfang Lyu, Zhihai He, Guitao Cao, and Zhiquan He, "Multimodal medical image registration based on feature spheres in geometric algebra." IEEE Access, Vol. 6pp. 21164-72, (2018).
29- Zongyun Gu, Li Cai, Yunxia Yin, Yatao Ding, and Hongxing Kan, "Registration of brain medical images based on surf algorithm and r-ransac algorithm." Telkomnika Indonesian Journal of Electrical Engineering, Vol. 12 (No. 3), pp. 2290-97, (2014).
30- Zong Yun Gu, Chun Min Du, Li Jin, and Hong Chun Tan, "Medical image registration combined with SURF and improved RANSAC algorithm." in Applied Mechanics and Materials, (2013), Vol. 411: Trans Tech Publ, pp. 1233-37.
31- Fan Guo, Xin Zhao, Beiji Zou, and Yixiong Liang, "Automatic retinal image registration using blood vessel segmentation and SIFT feature." International Journal of Pattern Recognition and Artificial Intelligence, Vol. 31 (No. 11), p. 1757006, (2017).
32- Nagham E Mekky, E-Z Fatma, and Sherif Kishk, "A new dental panoramic X-ray image registration technique using hybrid and hierarchical strategies." in The 2010 International Conference on Computer Engineering & Systems, (2010): IEEE, pp. 361-67.
33- Zeinab Ghassabi, Jamshid Shanbehzadeh, Ali Mohammadzadeh, and Seyed Shervin Ostadzadeh, "Colour retinal fundus image registration by selecting stable extremum points in the scale-invariant feature transform detector." IET Image Processing, Vol. 9 (No. 10), pp. 889-900, (2015).
34- Anqi Liu, "Eyeball Image Registration and Fusion Based on SIFT+ RANSAC Algorithm." Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology: Algorithms and Applications, Proceedings of IC3DIT 2019, Volume 2, Vol. 180p. 223, (2020).
35- Zahra Hossein-Nejad and Mehdi Nasri, "Retinal Image Registration based on Auto-Adaptive SIFT and Redundant Keypoint Elimination Method." in 2019 27th Iranian Conference on Electrical Engineering (ICEE), (2019): IEEE, pp. 1294-97.
36- Herbert Bay, Tinne Tuytelaars, and Luc Van Gool, "Surf: Speeded up robust features." in European conference on computer vision, (2006): Springer, pp. 404-17.
37- David G Lowe, "Distinctive image features from scale-invariant keypoints." International journal of computer vision, Vol. 60 (No. 2), pp. 91-110, (2004).
38- Z. Hossein-Nejad and M. Nasri, "Adaptive RANSAC and extended region-growing algorithm for object recognition over remote-sensing images." Multimedia Tools and Applications, (2022).
39- National Institutes of Health, "Retrospective Image Registration Evaluation." Vanderbilt University, Nashville (TN), USA, (2003).
40- Zahra Hossein-nejad and Mehdi Nasri, "Image Registration Based on Redundant Keypoint Elimination SARSIFT Algorithm and MROGH Descriptor." Presented at the The 12th Iranian and the second International Conference on Machine Vision and Image Processing, Shahid Chamran University of Ahvaz, Ahvaz, Iran, (2022).
2- Derek LG Hill, Philipp G Batchelor, Mark Holden, and David J Hawkes, "Medical image registration." Physics in medicine and biology, Vol. 46 (No. 3), p. R1, (2001).
3- MJ Velázquez-Durán, DU Campos-Delgado, ER Arce-Santana, and AR Mejía-Rodríguez, "Multimodal 3D rigid image registration based on expectation maximization." Health and Technology, Vol. 10 (No. 2), pp. 429-35, (2020).
4- Lvchen Cao, Huiqi Li, and Yanjun Zhang, "Retinal image enhancement using low-pass filtering and α-rooting." Signal Processing, Vol. 170p. 107445, (2020).
5- Zahra Hossein-Nejad and Mehdi Nasri, "Natural Image Mosaicing based on Redundant Keypoint Elimination Method in SIFT algorithm and Adaptive RANSAC method." (in eng), Signal and Data Processing, Research Vol. 18 (No. 2), pp. 147-62, (2021).
6- Zhenzhen Yang, Nan Kuang, Yongpeng Yang, and Bin Kang, "Brain MR Multimodal Medical Image Registration Based on Image Segmentation and Symmetric Self-similarity." KSII Transactions on Internet & Information Systems, Vol. 14 (No. 3), (2020).
7- Liang Shen, Xiaotao Huang, Chongyi Fan, and Yueli Li, "Enhanced mutual information-based medical image registration using a hybrid optimisation technique." Electronics Letters, Vol. 54 (No. 15), pp. 926-28, (2018).
8- Debapriya Sengupta, Phalguni Gupta, and Arindam Biswas, "A Survey on Mutual Information Based Medical Image Registration Algorithms." Neurocomputing, (2021).
9- Qian Zheng, Qiang Wang, Xiaojuan Ba, Shan Liu, Jiaofen Nan, and Shizheng Zhang, "A Medical Image Registration Method Based on Progressive Images." Computational and Mathematical Methods in Medicine, Vol. 2021(2021).
10- Roziana Ramli, Khairunnisa Hasikin, Mohd Yamani Idna Idris, Noor Khairiah A Karim, and Ainuddin Wahid Abdul Wahab, "Fundus Image Registration Technique Based on Local Feature of Retinal Vessels." Applied Sciences, Vol. 11 (No. 23), p. 11201, (2021).
11- Dwarikanath Mahapatra, Bhavna Antony, Suman Sedai, and Rahil Garnavi, "Deformable medical image registration using generative adversarial networks." in 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), (2018): IEEE, pp. 1449-53.
12- TJ Yang, Q Tang, L Li, and XH Bai, "Non-rigid medical image registration using multi-scale residual deep fully convolutional networks." Journal of Instrumentation, Vol. 16 (No. 03), p. P03005, (2021).
13- Yanjia Chen, Xiuwei Zhang, Yanning Zhang, Stephen John Maybank, and Zhipeng Fu, "Visible and infrared image registration based on region features and edginess." Machine Vision and Applications, Vol. 29 (No. 1), pp. 113-23, (2018).
14- Zahra Hossein-Nejad and Mehdi Nasri, "RKEM: Redundant Keypoint Elimination Method in Image Registration." IET Image Processing, Vol. 11 (No. 5), pp. 273-84, (2017).
15- Rousseau François, Ronan Fablet, and Christian Barillot, "Robust statistical registration of 3D ultrasound images using texture information." in Proceedings 2003 international conference on image processing (Cat. No. 03CH37429), (2003), Vol. 1: IEEE, pp. I-581.
16- Ahmadreza Baghaie and Zeyun Yu, "Curvature-based registration for slice interpolation of medical images." in International Symposium Computational Modeling of Objects Represented in Images, (2014): Springer, pp. 69-80.
17- Zeinab Ghassabi, Jamshid Shanbehzadeh, Amin Sedaghat, and Emad Fatemizadeh, "An efficient approach for robust multimodal retinal image registration based on UR-SIFT features and PIIFD descriptors." EURASIP Journal on Image and Video Processing, Vol. 2013 (No. 1), pp. 1-16, (2013).
18- Zahra Hossein-nejad and Mehdi Nasri, "Image registration based on SIFT features and adaptive RANSAC transform." in Communication and Signal Processing (ICCSP), 2016 International Conference on, (2016): IEEE, pp. 1087-91.
19- Zahra Hossein-Nejad and Mehdi Nasri, "A Review on Image Registration Methods, Concepts and applications." Journal of Machine Vision and Image Processing, pp. 39-67, (2017).
20- Zahra Hossein-Nejad and Mehdi Nasri, "Clustered redundant keypoint elimination method for image mosaicing using a new Gaussian-weighted blending algorithm." The Visual Computer, 2021/07/19 (2021).
21- Wendy Aguilar, Yann Frauel, Francisco Escolano, M Elena Martinez-Perez, Arturo Espinosa-Romero, and Miguel Angel Lozano, "A robust graph transformation matching for non-rigid registration." Image Vision Computing, Vol. 27 (No. 7), pp. 897-910, (2009).
22- Martin A Fischler and Robert C Bolles, "Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography." Communications of the ACM, Vol. 24 (No. 6), pp. 381-95, (1981).
23- Zahra Hossein-Nejad and Mehdi Nasri, "An adaptive image registration method based on SIFT features and RANSAC transform." Computers & Electrical Engineering, Vol. 62pp. 524-37, (2017).
24- Zahra Hossein-nejad and mehdi Nasri, "Adaptive Stopping Criteria-based A-RANSAC algorithm in Copy Move Image Forgery detection." Presented at the 12th International Conference on Information and Knowledge Technology (IKT2021), Mazandaran University of Science and Technology, Mazandaran, Iran, (2021).
25- Tiening Chen and Jianguang Zhuang, "Performance Evaluation of the Scale-Invariant Feature Transform in Different Modalities of Medical Image Registration." Frontiers in Computer Technology and Applications, Vol. 1 (No. 1), pp. 28-32, (2020).
26- PV Lukashevich, BA Zalesky, and SV Ablameyko, "Medical image registration based on surf detector." Pattern Recognition and Image Analysis, Vol. 21 (No. 3), pp. 519-21, (2011).
27- Blaine Rister, Mark A Horowitz, and Daniel L Rubin, "Volumetric image registration from invariant keypoints." IEEE transactions on image processing, Vol. 26 (No. 10), pp. 4900-10, (2017).
28- Wenming Cao, Fangfang Lyu, Zhihai He, Guitao Cao, and Zhiquan He, "Multimodal medical image registration based on feature spheres in geometric algebra." IEEE Access, Vol. 6pp. 21164-72, (2018).
29- Zongyun Gu, Li Cai, Yunxia Yin, Yatao Ding, and Hongxing Kan, "Registration of brain medical images based on surf algorithm and r-ransac algorithm." Telkomnika Indonesian Journal of Electrical Engineering, Vol. 12 (No. 3), pp. 2290-97, (2014).
30- Zong Yun Gu, Chun Min Du, Li Jin, and Hong Chun Tan, "Medical image registration combined with SURF and improved RANSAC algorithm." in Applied Mechanics and Materials, (2013), Vol. 411: Trans Tech Publ, pp. 1233-37.
31- Fan Guo, Xin Zhao, Beiji Zou, and Yixiong Liang, "Automatic retinal image registration using blood vessel segmentation and SIFT feature." International Journal of Pattern Recognition and Artificial Intelligence, Vol. 31 (No. 11), p. 1757006, (2017).
32- Nagham E Mekky, E-Z Fatma, and Sherif Kishk, "A new dental panoramic X-ray image registration technique using hybrid and hierarchical strategies." in The 2010 International Conference on Computer Engineering & Systems, (2010): IEEE, pp. 361-67.
33- Zeinab Ghassabi, Jamshid Shanbehzadeh, Ali Mohammadzadeh, and Seyed Shervin Ostadzadeh, "Colour retinal fundus image registration by selecting stable extremum points in the scale-invariant feature transform detector." IET Image Processing, Vol. 9 (No. 10), pp. 889-900, (2015).
34- Anqi Liu, "Eyeball Image Registration and Fusion Based on SIFT+ RANSAC Algorithm." Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology: Algorithms and Applications, Proceedings of IC3DIT 2019, Volume 2, Vol. 180p. 223, (2020).
35- Zahra Hossein-Nejad and Mehdi Nasri, "Retinal Image Registration based on Auto-Adaptive SIFT and Redundant Keypoint Elimination Method." in 2019 27th Iranian Conference on Electrical Engineering (ICEE), (2019): IEEE, pp. 1294-97.
36- Herbert Bay, Tinne Tuytelaars, and Luc Van Gool, "Surf: Speeded up robust features." in European conference on computer vision, (2006): Springer, pp. 404-17.
37- David G Lowe, "Distinctive image features from scale-invariant keypoints." International journal of computer vision, Vol. 60 (No. 2), pp. 91-110, (2004).
38- Z. Hossein-Nejad and M. Nasri, "Adaptive RANSAC and extended region-growing algorithm for object recognition over remote-sensing images." Multimedia Tools and Applications, (2022).
39- National Institutes of Health, "Retrospective Image Registration Evaluation." Vanderbilt University, Nashville (TN), USA, (2003).
40- Zahra Hossein-nejad and Mehdi Nasri, "Image Registration Based on Redundant Keypoint Elimination SARSIFT Algorithm and MROGH Descriptor." Presented at the The 12th Iranian and the second International Conference on Machine Vision and Image Processing, Shahid Chamran University of Ahvaz, Ahvaz, Iran, (2022).
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| Issue | Vol 10 No 2 (2023) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/fbt.v10i2.12216 | |
| Keywords | ||
| Brain Image Registration Clustered Redundant Keypoint Elimination Method - Scale Invariant Feature Transform Spatial Relations Redundant Keypoints Magnetic Resonance Imaging | ||
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How to Cite
1.
Hossein-Nejad Z, Nasri M. Clustered Redundant Keypoint Elimination SURF method in MRI Image Registration based on Alpha-Trimmed Relationship. Frontiers Biomed Technol. 2023;10(2):120-131.
