Scale Invariant Feature Transform as feature tracking method in 4D imaging: a feasibility study.
We propose the use of Scale Invariant Feature Transform (SIFT) as a method able to extract stable landmarks from 4D images and to quantify internal motion. We present a preliminary validation of the SIFT method relying on expert user identification of landmarks and then apply it to 4D lung CT and liver MRI data. Results demonstrate SIFT capabilities as an operator-independent feature tracking method.
Department of Bioengineering, Politecnico di Milano, Milano, Italy. chiara1.paganelli@ mail.polimi.it
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Paganelli
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Peroni
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Pennati
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Baroni
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Summers
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Bellomi
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Riboldi
D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008099:Liver / Q000473:pathology*; D008168:Lung / Q000000981:diagnostic imaging*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015233:Models, Statistical; D009068:Movement; D016011:Normal Distribution; D010363:Pattern Recognition, Automated / Q000379:methods*; D012984:Software; D013997:Time Factors; D014057:Tomography, X-Ray Computed / Q000379:methods*