SUPPRESSION OF SPECKLE NOISE IN MEDICAL IMAGES VIA SEGMENTATION-GROUPING OF 3D OBJECTS USING SPARSE CONTOURLET REPRESENTATION
- Авторлар: Kravchenko V.1,2, Guliaev Y.1, Ponomaryov V.3, Bojorges G.3
-
Мекемелер:
- Kotelnikov Institute of Radioengineering and Electronics of the Russian Academy of Sciences
- Bauman Moscow State Technical University
- Instituto Politecnico Nacional de Mexico
- Шығарылым: Том 509, № 1 (2023)
- Беттер: 94-100
- Бөлім: ИНФОРМАТИКА
- URL: https://journals.rcsi.science/2686-9543/article/view/142177
- DOI: https://doi.org/10.31857/S2686954322600562
- EDN: https://elibrary.ru/CQFBDY
- ID: 142177
Дәйексөз келтіру
Аннотация
Novel filtering method in medical images (MRI and US) that are contaminated by noise consisting of mixture speckle and additive noise is designed in this paper. Proposed method consists of several stages: segmentation of image areas, grouping of similar 2D structures in accordance mutual information (MI) measure, homomorphic transformation, 3D filtering approach based on sparse representation in contourlet (CLT) space with posterior filtering in accordance with MI weights similar 2D structures, and final inverse homomorphic transformation. During numerous experiments, the developed method has confirmed their superiority in term of visual image quality via human visual perception as well as in better criteria values, such as PSNR, SSIM, EPI and alfa for different test MRI and US mages corrupted by speckle noise.
Авторлар туралы
V. Kravchenko
Kotelnikov Institute of Radioengineering and Electronics of the Russian Academy of Sciences; Bauman Moscow State Technical University
Хат алмасуға жауапты Автор.
Email: kvf-ok@mail.ru
Russian Federation, Moscow; Russian Federation, Moscow
Yu. Guliaev
Kotelnikov Institute of Radioengineering and Electronics of the Russian Academy of Sciences
Хат алмасуға жауапты Автор.
Email: gulyaev@cplire.ru
Russian Federation, Moscow
V. Ponomaryov
Instituto Politecnico Nacional de Mexico
Хат алмасуға жауапты Автор.
Email: vponomar@ipn.mx
Mexico, Mexico
G. Bojorges
Instituto Politecnico Nacional de Mexico
Хат алмасуға жауапты Автор.
Email: gibran.aranda.bionics@gmail.com
Mexico, Mexico
Әдебиет тізімі
- Кравченко В.Ф., Пономарев В.И., Пустовойт В.И., Аранда-Бохоргес Г. // Доклады РАН. Математика, информатика, процессы управления. 2021. Т. 499. № 2. С. 67–72.
- Aranda-Bojorges G., Ponomaryov V., Reyes-Reyes R., Cruz-Ramos C., Sadovnychiy S. // IEEE Geosci. Rem. Sens. Lett. 2020. V. 19, art. 4018005. https://doi.org/10.1109/LGRS.2021.3108774
- Reyes-Reyes R., Aranda-Bojorges G., Garcia-Salgado B., Ponomaryov V., Cruz-Ramos C., Sadovnychiy S. // Sensors. 2022. V. 22. 5113. https://doi.org/10.3390/s22145113
- Kravchenko V., Perez H., Ponomaryov V. Adaptive Signal Processing of Multidimensional Signals with Applications. Moscow: Fizmatlit, 2009.
- Dabov K., Foi A., Katkovnik V., Egiazarian K. // IEEE Trans. Image Process. 2007. V. 16. № 8. P. 2080–2095.
- Santos C.A.N., Martins D.L.N., Mascarenhas N.D.A. // IEEE Trans. Image Process. 2017. V. 26. 2632–2643. https://doi.org/10.1109/TIP.2017.2685339
- Sameera V.M.S., Sudhish N.G. // Sensing Imaging. 2017. V. 18. P. 1–28. https://doi.org/10.1007/s11220-017-0181-8
- Jubairahmed L., Satheeskumaran S., Venkatesan C. // Clust. Comput. 2019. V. 22. P. 11237–11246.
- Jaburalla M.Y., Lee H.N. // Appl. Sci. 2018. V. 8. 903. P. 1–17. https://doi.org/10.3390/app8060903
- Achanta R., Shaji A., Smith K., Lucchi A., Fua P., Süsstrunk S. // IEEE Trans. Pattern Anal. Mach. Intell. 2012. V. 34. P. 2274–2282.
- Jensen J.A. // Med. Biol. Eng. Comput. 1996. V. 34. P. 351–352.
- Wang Z., Bovik A. // IEEE Signal Process. Mag. 2009. V. 26. № 1. P. 98–117.
- https://openfmri.org/dataset/ (accessed: June21, 2022).
- http://splab.cz/en/download/databaze/ultrasound (accessed: June 19, 2022).