Noise Estimation for MRI Images with Revised Theory on Histograms of Second-order Derivatives
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Abstract
Previous research by the author in the use of histograms of second-order derivatives showed that the differences between pixels in MRI images can be determined without referring to the ground truth for the purpose of noise reduction. Yet, the results of the previous research also showed that the methodologies used could not prevent false positives and negatives. A technique has been developed to involve multiple conditions that utilize the statistics of the histograms and the circumstances of neighbours in the vicinity of a pixel. The confusion matrix for this method shows that the technique has marginal but consistent improvement across the noise levels that are tested, compared to prior methods.
(Manuscript received: 8 October 2022 | Accepted: 27 April 2023 | Published: 30 April 2023)
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