LinkedIn

 آمار

تعداد نشریات20
تعداد شماره‌ها1,135
تعداد مقالات10,359
تعداد مشاهده مقاله43,952,228
تعداد دریافت فایل اصل مقاله9,881,773
Shirazinodeh, Alireza, Faraji, Hadis, Sharifzadeh Javidi, Sam, Jafari, Amir Homayoun, Nazemzadeh, Mohammadreza, Saligheh Rad, Hamidreza. (1403). Main Paths of Brain Fibers in Diffusion Images Mixed with a Noise to Improve Performance of Tractography Algorithm-Evaluation in Phantom. سامانه مدیریت نشریات علمی, 14(4), 357-364. doi: 10.31661/jbpe.v0i0.2108-1387
Alireza Shirazinodeh; Hadis Faraji; Sam Sharifzadeh Javidi; Amir Homayoun Jafari; Mohammadreza Nazemzadeh; Hamidreza Saligheh Rad. "Main Paths of Brain Fibers in Diffusion Images Mixed with a Noise to Improve Performance of Tractography Algorithm-Evaluation in Phantom". سامانه مدیریت نشریات علمی, 14, 4, 1403, 357-364. doi: 10.31661/jbpe.v0i0.2108-1387
Shirazinodeh, Alireza, Faraji, Hadis, Sharifzadeh Javidi, Sam, Jafari, Amir Homayoun, Nazemzadeh, Mohammadreza, Saligheh Rad, Hamidreza. (1403). 'Main Paths of Brain Fibers in Diffusion Images Mixed with a Noise to Improve Performance of Tractography Algorithm-Evaluation in Phantom', سامانه مدیریت نشریات علمی, 14(4), pp. 357-364. doi: 10.31661/jbpe.v0i0.2108-1387
Shirazinodeh, Alireza, Faraji, Hadis, Sharifzadeh Javidi, Sam, Jafari, Amir Homayoun, Nazemzadeh, Mohammadreza, Saligheh Rad, Hamidreza. Main Paths of Brain Fibers in Diffusion Images Mixed with a Noise to Improve Performance of Tractography Algorithm-Evaluation in Phantom. سامانه مدیریت نشریات علمی, 1403; 14(4): 357-364. doi: 10.31661/jbpe.v0i0.2108-1387

Main Paths of Brain Fibers in Diffusion Images Mixed with a Noise to Improve Performance of Tractography Algorithm-Evaluation in Phantom

Journal of Biomedical Physics and Engineering
دوره 14، شماره 4 - شماره پیاپی 66، مهر و آبان 2024، صفحه 357-364    اصل مقاله (1.58 M)
نوع مقاله: Original Research
شناسه دیجیتال (DOI): 10.31661/jbpe.v0i0.2108-1387
نویسندگان
Alireza Shirazinodeh1؛ Hadis Faraji2؛ Sam Sharifzadeh Javidi1؛ Amir Homayoun Jafari3، 1؛ Mohammadreza Nazemzadeh1، 2؛ Hamidreza Saligheh Rad* 1، 4
1Department of Medical Physics and Biomedical Engineering, Medicine School, Tehran University of Medical Sciences, Tehran, Iran
2Research Center for Molecular and Cellular Imaging Advanced Medical Technologies and Equipment, Tehran University of Medical Sciences, Tehran, Iran
3Research Center for Biomedical Technologies and Robotics (RCBTR) Tehran University of Medical Sciences, Tehran, Iran
4Quantitative Medical Imaging Systems Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
چکیده
Background: Some voxels may alter the tractography results due to unintentional alteration of noises and other unwanted factors.
Objective: This study aimed to investigate the effect of local phase features on tractography results providing data are mixed by a Gaussian or random distribution noise.
Material and Methods: In this simulation study, a mask was firstly designed based on the local phase features to decrease false-negative and -positive tractography results. The local phase features are calculated according to the local structures of images, which can be zero-dimensional, meaning just one point (equivalent to noise in tractography algorithm), a line (equivalent to a simple fiber), or an edge (equivalent to structures more complex than a simple fiber). A digital phantom evaluated the feasibility current model with the maximum complexities of configurations in fibers, including crossing fibers. In this paper, the diffusion images were mixed separately by a Gaussian or random distribution noise in 2 forms: a zero-mean noise and a noise with a mean of data.
Results: The local mask eliminates the pixels of unfitted values with the main structures of images, due to noise or other interferer factors. 
Conclusion: The local phase features of diffusion images are an innovative solution to determine principal diffusion directions.

تازه های تحقیق

Alireza Shirazinodeh (Google Scholar)

Hamidreza Saligheh (Google Scholar)

کلیدواژه‌ها
Diffusion Tractography؛ Diffusion Magnetic Resonance Imaging؛ Features؛ Gaussian Distribution؛ Local Phase؛ Noise؛ Feasibility Studies؛ Brain
سایر فایل های مرتبط با مقاله
مراجع
  1. Basser PJ, Mattiello J, LeBihan D. MR diffusion tensor spectroscopy and imaging. Biophys J. 1994;66(1):259-67. doi: 10.1016/S0006-3495(94)80775-1. PubMed PMID: 8130344. PubMed PMCID: PMC1275686.
  2. Tuch DS. Q-ball imaging. Magn Reson Med. 2004;52(6):1358-72. doi: 10.1002/mrm.20279. PubMed PMID: 15562495.
  3. Wedeen VJ, Hagmann P, Tseng WY, Reese TG, Weisskoff RM. Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging. Magn Reson Med. 2005;54(6):1377-86. doi: 10.1002/mrm.20642. PubMed PMID: 16247738.
  4. Tournier JD, Calamante F, Gadian DG, Connelly A. Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution. Neuroimage. 2004;23(3):1176-85. doi: 10.1016/j.neuroimage.2004.07.037. PubMed PMID: 15528117.
  5. Donahue CJ, Sotiropoulos SN, Jbabdi S, Hernandez-Fernandez M, et al. Using Diffusion Tractography to Predict Cortical Connection Strength and Distance: A Quantitative Comparison with Tracers in the Monkey. J Neurosci. 2016;36(25):6758-70. doi: 10.1523/JNEUROSCI.0493-16.2016. PubMed PMID: 27335406. PubMed PMCID: PMC4916250.
  6. Daducci A, Dal Palú A, Descoteaux M, Thiran JP. Microstructure Informed Tractography: Pitfalls and Open Challenges. Front Neurosci. 2016;10:247. doi: 10.3389/fnins.2016.00247. PubMed PMID: 27375412. PubMed PMCID: PMC4893481.
  7. Shirazinodeh A, Salighehrad H. Improving performance of tractography algorithm by using local phase features. In Proceedings of the 2021 ISMRM & SMRT; USA: ISMRM; 2021.
  8. McNab JA, Polimeni JR, Wang R, Augustinack JC, Fujimoto K, et al. Surface based analysis of diffusion orientation for identifying architectonic domains in the in vivo human cortex. Neuroimage. 2013;69:87-100. doi: 10.1016/j.neuroimage.2012.11.065. PubMed PMID: 23247190. PubMed PMCID: PMC3557597.
  9. Miller KL, Stagg CJ, Douaud G, Jbabdi S, Smith SM, Behrens TEJ, Jenkinson M, Chance SA, et al. Diffusion imaging of whole, post-mortem human brains on a clinical MRI scanner. Neuroimage. 2011;57(1):167-81. doi: 10.1016/j.neuroimage.2011.03.070. PubMed PMID: 21473920. PubMed PMCID: PMC3115068.
  10. Sotiropoulos SN, Hernández-Fernández M, Vu AT, Andersson JL, Moeller S, Yacoub E, et al. Fusion in diffusion MRI for improved fibre orientation estimation: An application to the 3T and 7T data of the Human Connectome Project. Neuroimage. 2016;134:396-409. doi: 10.1016/j.neuroimage.2016.04.014. PubMed PMID: 27071694. PubMed PMCID: PMC6318224.
  11. Uğurbil K, Xu J, Auerbach EJ, Moeller S, Vu AT, Duarte-Carvajalino JM, Lenglet C, Wu X, Schmitter S, et al. Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project. Neuroimage. 2013;80:80-104. doi: 10.1016/j.neuroimage.2013.05.012. PubMed PMID: 23702417. PubMed PMCID: PMC3740184.
  12. Ma X, Uğurbil K, Wu X. Denoise magnitude diffusion magnetic resonance images via variance-stabilizing transformation and optimal singular-value manipulation. Neuroimage. 2020;215:116852. doi: 10.1016/j.neuroimage.2020.116852. PubMed PMID: 32305566. PubMed PMCID: PMC7292796.
  13. McGibney G, Smith MR. An unbiased signal-to-noise ratio measure for magnetic resonance images. Med Phys. 1993;20(4):1077-8. doi: 10.1118/1.597004. PubMed PMID: 8413015.
  14. Sijbers J, Den Dekker AJ, Van Dyck D, Raman E. Estimation of signal and noise from Rician distributed data. In Proceedings of the International Conference on Signal Processing and Communications; Canaria, Spain; 1998. p. 140-2.
  15. Aja-Fernandez S, Alberola-Lopez C, Westin CF. Noise and signal estimation in magnitude MRI and Rician distributed images: a LMMSE approach. IEEE Trans Image Process. 2008;17(8):1383-98. doi: 10.1109/TIP.2008.925382. PubMed PMID: 18632347.
  16. Wiest-Daesslé N, Prima S, Coupé P, Morrissey SP, Barillot C. Rician noise removal by non-Local Means filtering for low signal-to-noise ratio MRI: applications to DT-MRI. Med Image Comput Comput Assist Interv. 2008;11(Pt 2):171-9. doi: 10.1007/978-3-540-85990-1_21. PubMed PMID: 18982603. PubMed PMCID: PMC2665702.
  17. Eichner C, Cauley SF, Cohen-Adad J, Möller HE, Turner R, Setsompop K, Wald LL. Real diffusion-weighted MRI enabling true signal averaging and increased diffusion contrast. Neuroimage. 2015;122:373-84. doi: 10.1016/j.neuroimage.2015.07.074. PubMed PMID: 26241680. PubMed PMCID: PMC4651971.
  18. Campbell JS, Pike GB. Potential and limitations of diffusion MRI tractography for the study of language. Brain Lang. 2014;131:65-73. doi: 10.1016/j.bandl.2013.06.007. PubMed PMID: 23910928.
  19. Poupon C, Rieul B, Kezele I, Perrin M, Poupon F, Mangin JF. New diffusion phantoms dedicated to the study and validation of high-angular-resolution diffusion imaging (HARDI) models. Magn Reson Med. 2008;60(6):1276-83. doi: 10.1002/mrm.21789. PubMed PMID: 19030160.
  20. Aganj I, Lenglet C, Jahanshad N, Yacoub E, Harel N, Thompson PM, Sapiro G. A Hough transform global probabilistic approach to multiple-subject diffusion MRI tractography. Med Image Anal. 2011;15(4):414-25. doi: 10.1016/j.media.2011.01.003. PubMed PMID: 21376655. PubMed PMCID: PMC3115463.
  21. Felsberg M, Sommer G. The monogenic signal. IEEE Transactions on Signal Processing. 2001;49(12):3136-44. doi: 10.1109/78.969520.
  22. Unser M, Sage D, Van De Ville D. Multiresolution monogenic signal analysis using the Riesz-Laplace wavelet transform. IEEE Trans Image Process. 2009;18(11):2402-18. doi: 10.1109/TIP.2009.2027628. PubMed PMID: 19605325.
  23. Leemans A, Sijbers J, Verhoye M, Van Der Linden A, Van Dyck D. Mathematical framework for simulating diffusion tensor MR neural fiber bundles. Magn Reson Med. 2005;53(4):944-53. doi: 10.1002/mrm.20418. PubMed PMID: 15799061.
  24. Fadnavis S, Batson J, Garyfallidis E. Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning. 34th Conference on Neural Information Processing Systems; Vancouver, Canada: NeurIPS; 2020.
  25. Moeller S, Pisharady PK, Ramanna S, Lenglet C, Wu X, Dowdle L, Yacoub E, Uğurbil K, Akçakaya M. NOise reduction with DIstribution Corrected (NORDIC) PCA in dMRI with complex-valued parameter-free locally low-rank processing. 2021;226:117539. doi: 10.1016/j.neuroimage.2020.117539. PubMed PMID: 33186723. PubMed PMCID: PMC7881933.
آمار
تعداد مشاهده مقاله: 161,579
تعداد دریافت فایل اصل مقاله: 364


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب