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M Mulet-Parada

Publications and source records attributed to M Mulet-Parada.

3 recordsLinked to original sources

Semi-automatic boundary detection to improve reporting of regional left ventricular function.

AIMS: The reporting of regional left ventricular function is based on subjective assessment of endocardial motion and thickening and has a significant learning curve. We hypothesized that the use of an semi-automatic boundary detection system generating images with superimposed moving endocardial borders and a fixed end-diastolic reference border could improve the reporting of regional function. METHODS: We obtained 58 resting contrast images of 15 patients and using a new boundary detection system (Quamus), generated images with superimposed endocardial borders. The contrast images, images with additional Quamus borders and Quamus borders alone were assessed by two level 1 and two level 2 echocardiographers. They scored regional function and results were compared to two level 3 experienced stress echocardiography readers. RESULTS: The addition of borders improved the agreement of level 1 echocardiographers (weighted Kappa increased from 0.55 to 0.64) but did not change for level 2 echocardiographers (0.63 to 0.64) and has the potential to be a useful training tool.

Contrast Media↗

2D+T acoustic boundary detection in echocardiography.

In this paper we address the problem of spatio-temporal acoustic boundary detection in echocardiography. We propose a phase-based feature detection method to be used as the front end to higher-level 2D+T/3D+T reconstruction algorithms. We develop a 2D+T version of this algorithm and illustrate its performance on some typical echocardiogram sequences. We show how our temporal-based algorithm helps to reduce the number of spurious feature responses due to speckle and provides feature velocity estimates. Further, our approach is intensity-amplitude invariant. This makes it particularly attractive for echocardiographic segmentation, where choosing a single global intensity-based edge threshold is problematic.

Acoustics↗

Evaluating a robust contour tracker on echocardiographic sequences.

In this paper we present an evaluation of a robust visual image tracker on echocardiographic image sequences. We show how the tracking framework can be customized to define an appropriate shape space that describes heart shape deformations that can be learnt from a training data set. We also investigate energy-based temporal boundary enhancement methods to improve image feature measurement. Results are presented demonstrating real-time tracking on real normal heart motion data sequences and abnormal synthesized and real heart motion data sequences. We conclude by discussing some of our current research efforts.

Algorithms↗