kernel smoothing in matlab: theory and practice of kernel smoothing Search Results


kernel smooth density estimate function  (MathWorks Inc)
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MathWorks Inc kernel smooth density estimate function
Kernel Smooth Density Estimate Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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kernel smoothing function  (MathWorks Inc)
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MathWorks Inc kernel smoothing function
Kernel Smoothing Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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gaussian filter matlab smooth3 function  (MathWorks Inc)
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MathWorks Inc gaussian filter matlab smooth3 function
Gaussian Filter Matlab Smooth3 Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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2d gaussian kernel  (MathWorks Inc)
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Fascicle filtering includes highlighting thin lines using a vessel enhancement filter (step 1.1f) and subsequent thresholding (step 1.2f). Aponeurosis filtering includes highlighting thick lines (step 1.1a), masking with a thresholded version of the original image (step 1.2a and step 1.3a), <t>Gaussian</t> smoothing (step 1.4a) and thresholding (step 1.5a). The results of the fascicle and aponeurosis filtering process are inputs for the fascicle angle determination (step 3) and aponeurosis detection respectively (step 2).
2d Gaussian Kernel, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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ksdensity function  (MathWorks Inc)
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MathWorks Inc ksdensity function
Fascicle filtering includes highlighting thin lines using a vessel enhancement filter (step 1.1f) and subsequent thresholding (step 1.2f). Aponeurosis filtering includes highlighting thick lines (step 1.1a), masking with a thresholded version of the original image (step 1.2a and step 1.3a), <t>Gaussian</t> smoothing (step 1.4a) and thresholding (step 1.5a). The results of the fascicle and aponeurosis filtering process are inputs for the fascicle angle determination (step 3) and aponeurosis detection respectively (step 2).
Ksdensity Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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kernel smoothing ksdensity matlab function  (MathWorks Inc)
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MathWorks Inc kernel smoothing ksdensity matlab function
Fascicle filtering includes highlighting thin lines using a vessel enhancement filter (step 1.1f) and subsequent thresholding (step 1.2f). Aponeurosis filtering includes highlighting thick lines (step 1.1a), masking with a thresholded version of the original image (step 1.2a and step 1.3a), <t>Gaussian</t> smoothing (step 1.4a) and thresholding (step 1.5a). The results of the fascicle and aponeurosis filtering process are inputs for the fascicle angle determination (step 3) and aponeurosis detection respectively (step 2).
Kernel Smoothing Ksdensity Matlab Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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3d smoothing gaussian kernel  (MathWorks Inc)
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MathWorks Inc 3d smoothing gaussian kernel
Fascicle filtering includes highlighting thin lines using a vessel enhancement filter (step 1.1f) and subsequent thresholding (step 1.2f). Aponeurosis filtering includes highlighting thick lines (step 1.1a), masking with a thresholded version of the original image (step 1.2a and step 1.3a), <t>Gaussian</t> smoothing (step 1.4a) and thresholding (step 1.5a). The results of the fascicle and aponeurosis filtering process are inputs for the fascicle angle determination (step 3) and aponeurosis detection respectively (step 2).
3d Smoothing Gaussian Kernel, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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ksdensity in matlab  (MathWorks Inc)
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MathWorks Inc ksdensity in matlab
Fascicle filtering includes highlighting thin lines using a vessel enhancement filter (step 1.1f) and subsequent thresholding (step 1.2f). Aponeurosis filtering includes highlighting thick lines (step 1.1a), masking with a thresholded version of the original image (step 1.2a and step 1.3a), <t>Gaussian</t> smoothing (step 1.4a) and thresholding (step 1.5a). The results of the fascicle and aponeurosis filtering process are inputs for the fascicle angle determination (step 3) and aponeurosis detection respectively (step 2).
Ksdensity In Matlab, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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smoothing kernel ksdensity  (MathWorks Inc)
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Fascicle filtering includes highlighting thin lines using a vessel enhancement filter (step 1.1f) and subsequent thresholding (step 1.2f). Aponeurosis filtering includes highlighting thick lines (step 1.1a), masking with a thresholded version of the original image (step 1.2a and step 1.3a), <t>Gaussian</t> smoothing (step 1.4a) and thresholding (step 1.5a). The results of the fascicle and aponeurosis filtering process are inputs for the fascicle angle determination (step 3) and aponeurosis detection respectively (step 2).
Smoothing Kernel Ksdensity, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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gaussian kernel  (MathWorks Inc)
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MathWorks Inc gaussian kernel
Fascicle filtering includes highlighting thin lines using a vessel enhancement filter (step 1.1f) and subsequent thresholding (step 1.2f). Aponeurosis filtering includes highlighting thick lines (step 1.1a), masking with a thresholded version of the original image (step 1.2a and step 1.3a), <t>Gaussian</t> smoothing (step 1.4a) and thresholding (step 1.5a). The results of the fascicle and aponeurosis filtering process are inputs for the fascicle angle determination (step 3) and aponeurosis detection respectively (step 2).
Gaussian Kernel, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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finite impulse response filter  (MathWorks Inc)
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MathWorks Inc finite impulse response filter
Fascicle filtering includes highlighting thin lines using a vessel enhancement filter (step 1.1f) and subsequent thresholding (step 1.2f). Aponeurosis filtering includes highlighting thick lines (step 1.1a), masking with a thresholded version of the original image (step 1.2a and step 1.3a), <t>Gaussian</t> smoothing (step 1.4a) and thresholding (step 1.5a). The results of the fascicle and aponeurosis filtering process are inputs for the fascicle angle determination (step 3) and aponeurosis detection respectively (step 2).
Finite Impulse Response Filter, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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nonparametric kernel smoothing with the bandwidth 10  (MathWorks Inc)
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MathWorks Inc nonparametric kernel smoothing with the bandwidth 10
Fascicle filtering includes highlighting thin lines using a vessel enhancement filter (step 1.1f) and subsequent thresholding (step 1.2f). Aponeurosis filtering includes highlighting thick lines (step 1.1a), masking with a thresholded version of the original image (step 1.2a and step 1.3a), <t>Gaussian</t> smoothing (step 1.4a) and thresholding (step 1.5a). The results of the fascicle and aponeurosis filtering process are inputs for the fascicle angle determination (step 3) and aponeurosis detection respectively (step 2).
Nonparametric Kernel Smoothing With The Bandwidth 10, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Fascicle filtering includes highlighting thin lines using a vessel enhancement filter (step 1.1f) and subsequent thresholding (step 1.2f). Aponeurosis filtering includes highlighting thick lines (step 1.1a), masking with a thresholded version of the original image (step 1.2a and step 1.3a), Gaussian smoothing (step 1.4a) and thresholding (step 1.5a). The results of the fascicle and aponeurosis filtering process are inputs for the fascicle angle determination (step 3) and aponeurosis detection respectively (step 2).

Journal: PLoS ONE

Article Title: TimTrack: A drift-free algorithm for estimating geometric muscle features from ultrasound images

doi: 10.1371/journal.pone.0265752

Figure Lengend Snippet: Fascicle filtering includes highlighting thin lines using a vessel enhancement filter (step 1.1f) and subsequent thresholding (step 1.2f). Aponeurosis filtering includes highlighting thick lines (step 1.1a), masking with a thresholded version of the original image (step 1.2a and step 1.3a), Gaussian smoothing (step 1.4a) and thresholding (step 1.5a). The results of the fascicle and aponeurosis filtering process are inputs for the fascicle angle determination (step 3) and aponeurosis detection respectively (step 2).

Article Snippet: Next, a second mask is applied to retain only the user-defined depth region for each aponeurosis and the remaining white pixels in each depth region (i.e. superficial and deep) are smoothed using a 2D Gaussian kernel ( imgaussfilt , MATLAB, step 1.4a, ) with a standard deviation of half an aponeurosis thickness (i.e. σ a p o 2 , see ), and thresholded (step 1.5a, ).

Techniques: