2d marker endpoint identification algorithm Search Results


2d marker endpoint identification algorithm  (MathWorks Inc)
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MathWorks Inc 2d marker endpoint identification algorithm
<t>2D</t> <t>marker</t> <t>endpoint</t> identification method. (a) A ROI selected on the kV projection image. (b) The Laplacian image of the selected ROI. (c) The orientation direction map (in unit of degree) of the ROI image in (a) after the marker template matching. A marker template (17×17 pixels) at the orientation of zero degree is shown in the right corner of (c). (d) Two marker pixel groups selected based on thresholds on (b), orientation classification on (c) and some other criteria. (e) Finally determined marker endpoints (red).
2d Marker Endpoint Identification Algorithm, 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 marker endpoint identification method. (a) A ROI selected on the kV projection image. (b) The Laplacian image of the selected ROI. (c) The orientation direction map (in unit of degree) of the ROI image in (a) after the marker template matching. A marker template (17×17 pixels) at the orientation of zero degree is shown in the right corner of (c). (d) Two marker pixel groups selected based on thresholds on (b), orientation classification on (c) and some other criteria. (e) Finally determined marker endpoints (red).

Journal: Physics in medicine and biology

Article Title: A method to reconstruct intra-fractional liver motion in rotational radiotherapy using linear fiducial markers

doi: 10.1088/1361-6560/ab4c0d

Figure Lengend Snippet: 2D marker endpoint identification method. (a) A ROI selected on the kV projection image. (b) The Laplacian image of the selected ROI. (c) The orientation direction map (in unit of degree) of the ROI image in (a) after the marker template matching. A marker template (17×17 pixels) at the orientation of zero degree is shown in the right corner of (c). (d) Two marker pixel groups selected based on thresholds on (b), orientation classification on (c) and some other criteria. (e) Finally determined marker endpoints (red).

Article Snippet: In the current Matlab based coding version, the computational time for the 2D marker endpoint identification algorithm to identify four marker endpoints from one projection was ~0.31 sec.

Techniques: Marker

Error distribution of the 2D marker endpoints along (a) u and (b) v directions.

Journal: Physics in medicine and biology

Article Title: A method to reconstruct intra-fractional liver motion in rotational radiotherapy using linear fiducial markers

doi: 10.1088/1361-6560/ab4c0d

Figure Lengend Snippet: Error distribution of the 2D marker endpoints along (a) u and (b) v directions.

Article Snippet: In the current Matlab based coding version, the computational time for the 2D marker endpoint identification algorithm to identify four marker endpoints from one projection was ~0.31 sec.

Techniques: Marker

RMS errors, 3D RMS error and percentage of time for motion errors exceeding 1.0 and 3.0 mm in simulation studies -- I. without noise in the 2D marker positions, II. with different levels of errors in 2D marker positions and III with an image acquisition frequency of every 0.3 sec, and in phantom experiments.

Journal: Physics in medicine and biology

Article Title: A method to reconstruct intra-fractional liver motion in rotational radiotherapy using linear fiducial markers

doi: 10.1088/1361-6560/ab4c0d

Figure Lengend Snippet: RMS errors, 3D RMS error and percentage of time for motion errors exceeding 1.0 and 3.0 mm in simulation studies -- I. without noise in the 2D marker positions, II. with different levels of errors in 2D marker positions and III with an image acquisition frequency of every 0.3 sec, and in phantom experiments.

Article Snippet: In the current Matlab based coding version, the computational time for the 2D marker endpoint identification algorithm to identify four marker endpoints from one projection was ~0.31 sec.

Techniques: Marker

Mean and standard deviation of rotational angle errors in simulation studies -- I. without noise in the 2D marker positions and II. with different levels of errors in 2D marker positions, and in phantom experiments.

Journal: Physics in medicine and biology

Article Title: A method to reconstruct intra-fractional liver motion in rotational radiotherapy using linear fiducial markers

doi: 10.1088/1361-6560/ab4c0d

Figure Lengend Snippet: Mean and standard deviation of rotational angle errors in simulation studies -- I. without noise in the 2D marker positions and II. with different levels of errors in 2D marker positions, and in phantom experiments.

Article Snippet: In the current Matlab based coding version, the computational time for the 2D marker endpoint identification algorithm to identify four marker endpoints from one projection was ~0.31 sec.

Techniques: Standard Deviation, Marker

Top row: marker trajectories reconstructed with the 6-DoF PM3 method and that of the ground truth, along (a1) LR, (a2) AP and (a3) SI directions, in a simulation study of TRM type assuming accurate 2D marker positions. Bottom row: the reconstruction errors along the three directions.

Journal: Physics in medicine and biology

Article Title: A method to reconstruct intra-fractional liver motion in rotational radiotherapy using linear fiducial markers

doi: 10.1088/1361-6560/ab4c0d

Figure Lengend Snippet: Top row: marker trajectories reconstructed with the 6-DoF PM3 method and that of the ground truth, along (a1) LR, (a2) AP and (a3) SI directions, in a simulation study of TRM type assuming accurate 2D marker positions. Bottom row: the reconstruction errors along the three directions.

Article Snippet: In the current Matlab based coding version, the computational time for the 2D marker endpoint identification algorithm to identify four marker endpoints from one projection was ~0.31 sec.

Techniques: Marker

Translation (top row) and rotation angle (bottom row) along LR, AP and SI directions in a representative simulation case with the standard deviation of 2D marker position error being 0.22 mm.

Journal: Physics in medicine and biology

Article Title: A method to reconstruct intra-fractional liver motion in rotational radiotherapy using linear fiducial markers

doi: 10.1088/1361-6560/ab4c0d

Figure Lengend Snippet: Translation (top row) and rotation angle (bottom row) along LR, AP and SI directions in a representative simulation case with the standard deviation of 2D marker position error being 0.22 mm.

Article Snippet: In the current Matlab based coding version, the computational time for the 2D marker endpoint identification algorithm to identify four marker endpoints from one projection was ~0.31 sec.

Techniques: Standard Deviation, Marker

The illustration of the performance of the 2D marker identification algorithm to identify markers with overlap. (a) The kV projection data and (b) the corresponding marker identification results. Points labeled with 1 (yellow) and 2 (blue) are the two markers while the ones labeled with 3 (white) are the overlapped region.

Journal: Physics in medicine and biology

Article Title: A method to reconstruct intra-fractional liver motion in rotational radiotherapy using linear fiducial markers

doi: 10.1088/1361-6560/ab4c0d

Figure Lengend Snippet: The illustration of the performance of the 2D marker identification algorithm to identify markers with overlap. (a) The kV projection data and (b) the corresponding marker identification results. Points labeled with 1 (yellow) and 2 (blue) are the two markers while the ones labeled with 3 (white) are the overlapped region.

Article Snippet: In the current Matlab based coding version, the computational time for the 2D marker endpoint identification algorithm to identify four marker endpoints from one projection was ~0.31 sec.

Techniques: Marker, Labeling