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19. Exploring the Stationary Wavelet Transform detail coefficients for detection and identification of the S1 and S2 heart sounds.

Author

Marques, N, Almeida, Rute, Rocha, Ana Paula, and Coimbra, M

Abstract

Most work done in Heart Sound Segmentation approaches use a threshold-based approach to correctly identify S1 and S2 segments in a given signal. We propose a new method that uses the Stationary Wavelet Transform to segment the signal and hierarchical clustering to distinguish the S1 and S2 heart sound from noise. This approach was tested in the Classifying Heart Sounds PASCAL Challenge datasets and achieved better results than the winning approach of this contest, with a total error redcution of 21% and 43% for Digiscope and iStethoscope in test sets, respectively. [ABSTRACT FROM PUBLISHER]

Published
2013

21. Automated Topographic Segmentation and Transit Time Estimation in Endoscopic Capsule Exams.

Author

Silva Cunha, J. P., Coimbra, M., Campos, P., and Soares, J. M.

Subjects
*CAPSULE endoscopy, *ENDOSCOPY, *DIAGNOSTIC imaging, *MEDICAL imaging systems, EXAMINATION of the gastrointestinal system
Abstract

Endoscopic capsule is a recent medical technology with important clinical benefits but suffering from a practical handicap: long exam annotation times. This paper proposes and compares two approaches (Bayesian and support vector machines) that can be used to segment the gastrointestinal tract into its four major topographic areas, allowing the automatic estimation of the clinically relevant gastric and intestinal sections and corresponding transit times. According to medical specialists, this can reduce exam annotation times by up to 12% (15 min). This automatic tool has been integrated into our CapView annotation software that is currently being used by three medical institutions. [ABSTRACT FROM AUTHOR]

Published
2008
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