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		<citationkey>MatsumotoLemoYoneFuru:2007:CaPhDe</citationkey>
		<title>Cardiac Phase Detection in Intravascular Ultrasound Images</title>
		<format>On-line</format>
		<year>2007</year>
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		<author>Matsumoto, Monica Mitiko Soares,</author>
		<author>Lemos, Pedro Alves,</author>
		<author>Yoneyama, Takashi,</author>
		<author>Furuie, Sérgio Shiguemi,</author>
		<affiliation>Aeronautics Institute of Technology (ITA), São José dos Campos, Brazil and Heart Institute (InCor), Medical School, University of São Paulo, Brazil</affiliation>
		<affiliation>Heart Institute (InCor), Medical School, University of São Paulo, Brazil</affiliation>
		<affiliation>Aeronautics Institute of Technology (ITA), São José dos Campos, Brazil</affiliation>
		<affiliation>Heart Institute (InCor), Medical School, University of São Paulo, Brazil</affiliation>
		<editor>Gonçalves, Luiz,</editor>
		<editor>Wu, Shin Ting,</editor>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI)</conferencename>
		<conferencelocation>Belo Horizonte, MG, Brazil</conferencelocation>
		<date>7-10 Oct. 2007</date>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<publisheraddress>Porto Alegre</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Technical Poster</tertiarytype>
		<transferableflag>1</transferableflag>
		<keywords>Medical Image Processing, Intravascular Ultrasound, Signal Processing, Cardiac Phase.</keywords>
		<abstract>Image gating is a problem related to image modalities which involve quasi-periodic moving organs, such as the heart. Therefore, during intravascular ultrasound (IVUS) examination, with automatic pullback, there is cardiac movement interference. This work aims to obtain gated images based on the images themselves, so it would be possible to reconstruct 3D coronaries with temporal accuracy. From the images, we extracted signals based on average intensity (AI), and, from consecutive frames, average intensity difference (AID), crosscorrelation coefficient (CC) and a new approach using mutual information (MI). Firstly, our method was tested in simulated images, with different speckle noise level, contrast and patients characteristics. The results have shown our method was able to achieve more than 95.0% of true positives and 2.3% of false positives, for all signals. Afterwards, we tested in a real IVUS examination, with ECG as gold-standard, where there were achieved 97.4% of true positives (CC and MI), and 2.5% of false positives.</abstract>
		<language>en</language>
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