Key result
An automated method for detecting cardiac phase from intracoronary ultrasound image sequences achieved an average inter-frame dissimilarity lower than 0.1 and average frame processing time <30 ms.
The proposed automated method for detecting cardiac phase from non-gated ICUS image sequences is computationally efficient and effectively reduces the impact of image noise and non-cardiac factors.
Hypothesis-generating for automated ICUS phase detection; prospective clinical validation required before adoption.
Intracoronary ultrasound (ICUS) is a widely used interventional imaging modality in clinical diagnosis and treatment of cardiac vessel diseases. Due to cyclic cardiac motion and pulsatile blood flow within the lumen, there exist changes of coronary arterial dimensions and relative motion between the imaging catheter and the lumen during continuous pullback of the catheter. The action subsequently causes cyclic changes to the image intensity of the acquired image sequence. Information on cardiac phases is implied in a non-gated ICUS image sequence. A 1-D phase signal reflecting cardiac cycles was extracted according to cyclical changes in local gray-levels in ICUS images. The local extrema of the signal were then detected to retrieve cardiac phases and to retrospectively gate the image sequence. Results of clinically acquired in vivo image data showed that the average inter-frame dissimilarity of lower than 0.1 was achievable with our technique. In terms of computational efficiency and complexity, the proposed method was shown to be competitive when compared with the current methods. The average frame processing time was lower than 30 ms. We effectively reduced the effect of image noises, useless textures, and non-vessel region on the phase signal detection by discarding signal components caused by non-cardiac factors.
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Zheng et al. (2015) studied Cardiac vessel diseases. Automated detection of cardiac phase from intracoronary ultrasound image sequences vs. Current methods was evaluated on Average inter-frame dissimilarity and average frame processing time. An automated method for detecting cardiac phase from intracoronary ultrasound image sequences achieved an average inter-frame dissimilarity lower than 0.1 and average frame processing time <30 ms.
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