zhpsЖурнал прикладной спектроскопииZhurnal Prikladnoii Spektroskopii0514-7506B. I. Stepanov Institute of Physics of the National Academy of Scienceszhps-1066Research ArticleАННОТАЦИИ АНГЛОЯЗЫЧНЫХ СТАТЕЙABSTRACTS ENGLISH-LANGUAGE ARTICLESКритерий пороговой обработки на основе разреженности для удаления паразитного эха и шумоподавления магнитно-резонансных спектров с использованием расширенного вейвлет-преобразованияSparsity-Based Thresholding Criterion for Spurious Echo Removal and Denoising Magnetic Resonance Spectra Using Rational-Dilation Wavelet TransformSagarCh.SagarCh.

Варанаси, Уттар-Прадеш

Varanasi, Uttar Pradesh

chiranjeevs.rs.bme16@itbhu.ac.inKumar SinghD.Kumar SinghD.

Варанаси, Уттар-Прадеш

Varanasi, Uttar Pradesh

SharmaN.SharmaN.

Варанаси, Уттар-Прадеш

Varanasi, Uttar Pradesh

Школа биомедицинской инженерии Индийского технологического института (BHU)School of Biomedical Engineering at Indian Institute of Technology (BHU)Специализированная больница Apex и Институт последипломного образованияDepartment of Oncology, Apex Super-Speciality Hospital and Post Graduate Institute202226052022893430430Copyright © Sagar C., Kumar Singh D., Sharma N., 20222022Sagar C., Kumar Singh D., Sharma N.Sagar C., Kumar Singh D., Sharma N.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://zhps.ejournal.by/jour/article/view/1066

Предложена стратегия шумоподавления с использованием разложения сигнала на основе расширенного вейвлет-преобразования и критерия пороговых значений, разработанного с использованием меры разреженности на основе Lpq-нормы уровней разложения сигнала. По сравнению со стандартными современными методами, которые эффективны при шумоподавлении, но могут вызывать искажение сигнала при нарушениях непрерывности, предлагаемый метод может удалить артефакты, например ложные эхо-сигналы, и улучшить отношение сигнал/шум без искажения сигнала.

Biological signals such as magnetic resonance spectroscopy (MRS) signals are susceptible to noise and artifacts. The information obtained from these signals is significant in analyzing human physiological conditions. MRS, a non-ionizing and non-invasive method, presents an effective alternative method to biopsy for diagnosis and analysis from generated signals that are rich in chemical information of the tissues in the region of interest. A persisting problem of this method is the presence of noise and artifacts causing misinterpretation and subsequent incorrect diagnosis. The present research proposes a denoising strategy using the rational-dilation wavelet transform-based signal decomposition and a thresholding criterion designed using the Lpq norm-based sparsity measure of the decomposition levels of the signal. Compared with the standard state-of-the-art methods, which are effective in denoising but can cause distortion of the signal at discontinuities, the proposed method can remove artifacts such as spurious echoes present in the magnetic resonance signals and improve the signal-to-noise ratio without distorting the signal.

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The authors declare that there are no conflicts of interest present.