Automatic detection and classification of human epicardial atrial unipolar electrograms.

This paper describes an unsupervised signal processing method applied to three-channel unipolar electrograms recorded from human atria. These were obtained by epicardial wires sutured on the right and left atria after coronary artery bypass surgery. Atrial (A) and ventricular (V) activations had to be detected and identified on each channel, and gathered across the channels when belonging to the same global event. The algorithm was developed and optimized on a training set of 19 recordings of 5 min. It was assessed on twenty-seven 2 h recordings taken just before the onset of a prolonged atrial fibrillation for a total of 1593697 activations that were validated and classified as normal atrial or ventricular activations (A, V) and premature atrial or ventricular activations (PAA, PVA). 99.93% of the activations were detected, and amongst these, 99.89% of the A and 99.75% of the V activations were correctly labelled. In the subset of the 39705 PAA, 99.83% were detected and 99.3% were correctly classified as A. The false positive rate was 0.37%. In conclusion, a reliable fully automatic detection and classification algorithm was developed that can detect and discriminate A and V activations from atrial recordings. It can provide the time series needed to develop a monitoring system aiming to identify dynamic predictors of forthcoming cardiac events such as postoperative atrial fibrillation.

The effect of compression on clinical diagnosis of glaucoma based on non-analyzed confocal scanning laser ophthalmoscopy images.

BACKGROUND AND OBJECTIVE: To evaluate the effect of different image compression formats of non-analyzed Heidelberg Retina Tomography (HRT; Heidelberg Engineering, Heidelberg, Germany) images on the diagnosis of glaucoma by ophthalmologists. MATERIALS AND METHODS: Thirty-three topographic and reflectance images taken with the HRT representing different levels of disease were transformed using nine different compression formats. Three independent ophthalmologists, masked as to contour line and stereometric parameters, classified the original and compressed HRT images as normal, suspected glaucoma, or glaucoma, and Kappa agreement coefficients were calculated. RESULTS: The Tagged Image File Format had the largest file size and the Joint Photographic Experts Group (JPEG) 2000 format had the smallest size. The highest Kappa coefficient value was 1.00 for all ophthalmologists using the Tagged Image File Format. Kappa values for JPEG formats were all in the range of good to excellent agreement. Kappa values were lower for Portable Network Graphic and Graphics Interchange Format compression formats. CONCLUSION: Image compression with JPEG 2000 at a ratio of 20:1 provided sufficient quality for glaucoma analysis in conjunction with a relatively small image size format, and may prove to be attractive for HRT telemedicine applications. Further clinical studies validating the usefulness of interpreting non-analyzed HRT images are required.