Application of Noise Reduction Algorithm ClearVoice in Cochlear Implant Processing

2015 ◽  
Vol 36 (3) ◽  
pp. 357-367 ◽  
Author(s):  
J. Gertjan Dingemanse ◽  
André Goedegebure
Keyword(s):  
Cochlear Implant ◽  
Noise Reduction ◽  
Reduction Algorithm ◽  
Noise Reduction Algorithm

Impact of Noise Reduction Algorithm in Cochlear Implant Processing on Music Enjoyment

2016 ◽  
Vol 37 (5) ◽  
pp. 492-498 ◽  
Author(s):  
Gavriel D. Kohlberg ◽  
Dean M. Mancuso ◽  
Brianna M. Griffin ◽  
Jaclyn B. Spitzer ◽  
Anil K. Lalwani
Keyword(s):  
Cochlear Implant ◽  
Noise Reduction ◽  
Reduction Algorithm ◽  
Noise Reduction Algorithm

scholarly journals Evaluation of a transient noise reduction algorithm in cochlear implant users

2015 ◽  
Vol 5 (2) ◽  
Author(s):  
Karl-Heinz Dyballa ◽  
Phillipp Hehrmann ◽  
Volkmar Hamacher ◽  
Waldo Nogueira ◽  
Thomas Lenarz ◽  
...  
Keyword(s):  
Cochlear Implant ◽  
Noise Reduction ◽  
Reduction Algorithm ◽  
Subjective Ratings ◽  
Speech Reception ◽  
Age Range ◽  
Speech Clarity ◽  
Noise Reduction Algorithm

Dealing with environmental noises presents a major issue for cochlear implant (CI) users. Hence, digital noise reduction (DNR) schemes have become important features of CI systems. Many noises like for example clinking glasses or slamming doors, have impulsive onsets and decay quickly. Common DNR algorithms cannot handle this type of noise in an appropriate way. In this study, we investigated the effect of an algorithm specially designed for such noises with 12 CI users (age range: 45 to 75 years). Speech scores in noise and quiet as well as subjective ratings of speech clarity, comfort and overall preference were measured. The main finding was a significant improvement of up to 1.7 dB of the speech reception threshold in noise as well as increased speech clarity. Speech in quiet was not negatively affected by the algorithm. The study revealed that the tested algorithm has the potential to improve CI listening. However, further research is needed regarding the effectiveness and suitability of the algorithm in daily use.

scholarly journals Personalizing Transient Noise Reduction Algorithm Settings for Cochlear Implant Users

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
H. Christiaan Stronks ◽  
Annemijn L. Tops ◽  
Phillipp Hehrmann ◽  
Jeroen J. Briaire ◽  
Johan H. M. Frijns
Keyword(s):  
Cochlear Implant ◽  
Noise Reduction ◽  
Reduction Algorithm ◽  
Noise Reduction Algorithm

scholarly journals Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom Study

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 319
Author(s):  
Chan-Rok Park ◽  
Seong-Hyeon Kang ◽  
Young-Jin Lee
Keyword(s):  
Image Quality ◽  
Noise Reduction ◽  
Total Variation ◽  
Parallel Imaging ◽  
Pulse Sequence ◽  
Reduction Algorithm ◽  
Median Filters ◽  
Reduction Techniques ◽  
Imaging Results ◽  
Noise Reduction Algorithm

Recently, the total variation (TV) algorithm has been used for noise reduction distribution in degraded nuclear medicine images. To acquire positron emission tomography (PET) to correct the attenuation region in the PET/magnetic resonance (MR) system, the MR Dixon pulse sequence, which is based on controlled aliasing in parallel imaging, results from higher acceleration (CAIPI; MR-ACDixon-CAIPI) and generalized autocalibrating partially parallel acquisition (GRAPPA; MR-ACDixon-GRAPPA) algorithms are used. Therefore, this study aimed to evaluate the image performance of the TV noise reduction algorithm for PET/MR images using the Jaszczak phantom by injecting 18F radioisotopes with PET/MR, which is called mMR (Siemens, Germany), compared with conventional noise-reduction techniques such as Wiener and median filters. The contrast-to-noise (CNR) and coefficient of variation (COV) were used for quantitative analysis. Based on the results, PET images with the TV algorithm were improved by approximately 7.6% for CNR and decreased by approximately 20.0% for COV compared with conventional noise-reduction techniques. In particular, the image quality for the MR-ACDixon-CAIPI PET image was better than that of the MR-ACDixon-GRAPPA PET image. In conclusion, the TV noise-reduction algorithm is efficient for improving the PET image quality in PET/MR systems.

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