scholarly journals A New Idea of Fast Three-Dimensional Median Filtering for Despeckling of Optical Coherence Tomography Images

2015 ◽  
Vol 20 (3) ◽  
pp. 25-34 ◽  
Author(s):  
Jarosław Gocławski ◽  
Joanna Sekulska-Nalewajko
Keyword(s):  
Optical Coherence Tomography ◽  
Graphics Processing Unit ◽  
Median Filter ◽  
Three Dimensional ◽  
Speckle Noise ◽  
Noise Removal ◽  
Processing Unit ◽  
Optical Coherence ◽  
Median Filtering ◽  
Local Intensity

Abstract Median filtering has been widely used in image processing for noise removal because it can significantly reduce the power of noise while limiting edge blurring. This filtering is still a challenging task in the case of three-dimensional images containing up to a billion of voxels, especially for large size filtering windows. The authors encountered the problem when applying median filter to speckle noise reduction in optical coherence tomography images acquired by the Spark OCT systems. In the paper a new approach to the GPU (Graphics Processing Unit) based median smoothing has been proposed, which uses two-step evaluation of local intensity histograms stored in the shared memory of a graphic device. The solution is able to output about 50 million voxels per second while processing the neighbourhood of 125 voxels by Quadro K6000 graphic card configured on the Kepler architecture.

scholarly journals Three-dimensional curvelet-based dictionary learning for speckle noise removal of optical coherence tomography

2020 ◽  
Vol 11 (2) ◽  
pp. 586
Author(s):  
Mahad Esmaeili ◽  
Alireza Mehri Dehnavi ◽  
Fedra Hajizadeh ◽  
Hossein Rabbani
Keyword(s):  
Optical Coherence Tomography ◽  
Dictionary Learning ◽  
Three Dimensional ◽  
Speckle Noise ◽  
Noise Removal ◽  
Optical Coherence

scholarly journals Real-time speckle variance swept-source optical coherence tomography using a graphics processing unit

2012 ◽  
Vol 3 (7) ◽  
pp. 1557 ◽  
Author(s):  
Kenneth K. C. Lee ◽  
Adrian Mariampillai ◽  
Joe X. Z. Yu ◽  
David W. Cadotte ◽  
Brian C. Wilson ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Real Time ◽  
Graphics Processing Unit ◽  
Processing Unit ◽  
Optical Coherence ◽  
Swept Source ◽  
Graphics Processing

scholarly journals Application of fuzzy logic in finding the optimal filter in optoacoustics problems

2021 ◽  
pp. 43-54
Author(s):  
A. G. Rudnitskii ◽  
M. A. Rudnytska ◽  
L. V. Tkachenko ◽  
E. D. Pechuk
Keyword(s):  
Medical Practice ◽  
Early Stage ◽  
Median Filter ◽  
A Priori ◽  
Three Dimensional ◽  
Speckle Noise ◽  
Noise Removal ◽  
Arithmetic Mean ◽  
Optimal Filter ◽  
Mean Filter

Denoising is an important step in the early stage of signal preprocessing in optoacoustic applications. The efficiency of such modern noise removal methods as wavelet or curvlet filtering depends significantly on the numerical combinations and forms of wavelet transform parameters, and the multidimensional extension of such filters is rather non-trivial. These issues are serious obstacle for using of these highly effective filters in the tasks of optoacoustic reconstruction, especially in real laboratorial or medical practice. The objective of our study was to find the optimal filter, convenient for use in laboratorian and medical practice, when the types of noise are a priori unknown, and the filter settings should not take much time. In the offered work spatial filters which have only one parameter of adjustment - the size of a window are considered. Three-dimensional extensions of such well-established denoising techniques, as mean filter, median filter, their adaptive variants (Wiener spatial filter and modified median filter), as well as iterative truncated arithmetic mean filter were analyzed. The proposed filters were tested on a test set that contains versions of Shepp-Logan's three-dimensional phantom with mixtures of Gaussian and alpha-stable noise, as well as speckle noise. The identification of the best filter for simultaneous suppression of these types of interference was carried out using the theory of fuzzy sets. In our tests, a modified median filter and an iterative truncated arithmetic mean filter were rated as the best choice when the goal is to minimize aberrations when noise is not known a priory.

Sign in / Sign up

Export Citation Format

Share Document