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Author |
Hanne Kause; Aura Hernandez-Sabate; Patricia Marquez; Andrea Fuster; Luc Florack; Hans van Assen; Debora Gil |
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Title |
Confidence Measures for Assessing the HARP Algorithm in Tagged Magnetic Resonance Imaging |
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Book Chapter |
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Year |
2015 |
Publication |
Statistical Atlases and Computational Models of the Heart. Revised selected papers of Imaging and Modelling Challenges 6th International Workshop, STACOM 2015, Held in Conjunction with MICCAI 2015 |
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9534 |
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Pages |
69-79 |
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Abstract |
Cardiac deformation and changes therein have been linked to pathologies. Both can be extracted in detail from tagged Magnetic Resonance Imaging (tMRI) using harmonic phase (HARP) images. Although point tracking algorithms have shown to have high accuracies on HARP images, these vary with position. Detecting and discarding areas with unreliable results is crucial for use in clinical support systems. This paper assesses the capability of two confidence measures (CMs), based on energy and image structure, for detecting locations with reduced accuracy in motion tracking results. These CMs were tested on a database of simulated tMRI images containing the most common artifacts that may affect tracking accuracy. CM performance is assessed based on its capability for HARP tracking error bounding and compared in terms of significant differences detected using a multi comparison analysis of variance that takes into account the most influential factors on HARP tracking performance. Results showed that the CM based on image structure was better suited to detect unreliable optical flow vectors. In addition, it was shown that CMs can be used to detect optical flow vectors with large errors in order to improve the optical flow obtained with the HARP tracking algorithm. |
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Munich; Germany; January 2015 |
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Publisher |
Springer International Publishing |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-319-28711-9 |
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Conference |
STACOM |
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Notes |
ADAS; IAM; 600.075; 600.076; 600.060; 601.145 |
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Call Number |
Admin @ si @ KHM2015 |
Serial |
2734 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
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Title |
A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth |
Type |
Conference Article |
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Year |
2011 |
Publication |
IEEE International Conference on Computer Vision – Workshops |
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Pages |
2042-2049 |
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Keywords |
IEEE International Conference on Computer Vision – Workshops |
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Abstract |
Optical flow is a valuable tool for motion analysis in autonomous navigation systems. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in real world sequences. This paper introduces a measure of optical flow accuracy for Lucas-Kanade based flows in terms of the numerical stability of the data-term. We call this measure optical flow condition number. A statistical analysis over ground-truth data show a good statistical correlation between the condition number and optical flow error. Experiments on driving sequences illustrate its potential for autonomous navigation systems. |
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Publisher |
IEEE |
Place of Publication |
Barcelona (Spain) |
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Language |
English |
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English |
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Conference |
ICCVW |
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Notes |
IAM; ADAS |
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no |
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Call Number |
IAM @ iam @ MGH2011 |
Serial |
1682 |
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Author |
Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate |
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Title |
Error Analysis for Lucas-Kanade Based Schemes |
Type |
Conference Article |
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Year |
2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
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Volume |
7324 |
Issue |
I |
Pages |
184-191 |
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Keywords |
Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance |
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Abstract |
Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures. |
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Address |
Aveiro, Portugal |
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Springer-Verlag Berlin Heidelberg |
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english |
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Series Editor |
Campilho, Aurélio and Kamel, Mohamed |
Series Title |
Lecture Notes in Computer Science |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-31294-6 |
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ICIAR |
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IAM |
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no |
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Call Number |
IAM @ iam @ MGH2012a |
Serial |
1899 |
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