6 resultados para segmentation and reverberation
em Universidad de Alicante
Resumo:
We present new tools for the segmentation and analysis of musical scores in the OpenMusic computer-aided composition environment. A modular object-oriented framework enables the creation of segmentations on score objects and the implementation of automatic or semi-automatic analysis processes. The analyses can be performed and displayed thanks to customizable classes and callbacks. Concrete examples are given, in particular with the implementation of a semi-automatic harmonic analysis system and a framework for rhythmic transcription.
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Póster presentado en OPTYKA Optical Fair 2012, Poznan, Polonia, 9-10 noviembre 2012.
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In the advent of Customer Relationship Management, a more accurate profile of the consumer is needed. The objective of this paper is to show the usefulness of knowing consumer’s complete utility function through his/her marginal utilities. This approach allows one to form groups of individuals with similar preferences (as traditional segmentation methods do) and to treat them individually (which represents an advance). The empirical application is carried out, on a sample of 2,127 individuals, in the context of tourism, where the customer relationship management philosophy is gaining more and more relevance.
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Purpose: To evaluate choroidal thickness in young subjects using Enhanced Depth Imaging Spectral Domain Optical Coherence Tomography (EDI SD-OCT) describing volume differences between all the defined areas of the Early Treatment Diabetic Retinopathy Study (ETDRS). Design: Prospective, clinical study. Methods: Seventy-nine eyes of 95 healthy, young (23.8±3.2years), adult volunteers were prospectively enrolled. Manual choroidal segmentation on a 25-raster horizontal scan protocol was performed. The measurements of the nine subfields defined by the ETDRS were evaluated. Results: Mean subfoveal choroidal thickness was 345.67±81.80μm and mean total choroidal volume was 8.99±1.88mm3. Choroidal thickness and volume were higher at the superior and temporal areas compared to inferior and nasal sectors of the same diameter respectively. Strong correlations between subfoveal choroidal thickness and axial length (AL) and myopic refractive error were obtained, r = -0.649, p<0.001 and r = 0.473, p<0.001 respectively. Emmetropic eyes tended to have thicker subfoveal choroidal thickness (381.94±79.88μm versus 307.04±64.91μm) and higher total choroidal volume than myopic eyes (9.80± 1.87mm3 versus 8.14±1.48mm3). The estimation of the variation of the subfoveal choroidal thickness with the AL was-43.84μm/mm. In the myopic group, the variation of the subfoveal choroidal thickness with the myopic refractive error was -10.45μm/D. Conclusions: This study establishes for the first time a normal database for choroidal thickness and volume in young adults. Axial length, and myopic ammetropy are highly associated with choroidal parameters in healthy subjects. EDI SD-OCT exhibited a high degree of intraobserver and interobserver repeatability.
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A MATLAB-based computer code has been developed for the simultaneous wavelet analysis and filtering of several environmental time series, particularly focused on the analyses of cave monitoring data. The continuous wavelet transform, the discrete wavelet transform and the discrete wavelet packet transform have been implemented to provide a fast and precise time–period examination of the time series at different period bands. Moreover, statistic methods to examine the relation between two signals have been included. Finally, the entropy of curves and splines based methods have also been developed for segmenting and modeling the analyzed time series. All these methods together provide a user-friendly and fast program for the environmental signal analysis, with useful, practical and understandable results.
Resumo:
Abdominal Aortic Aneurism is a disease related to a weakening in the aortic wall that can cause a break in the aorta and the death. The detection of an unusual dilatation of a section of the aorta is an indicative of this disease. However, it is difficult to diagnose because it is necessary image diagnosis using computed tomography or magnetic resonance. An automatic diagnosis system would allow to analyze abdominal magnetic resonance images and to warn doctors if any anomaly is detected. We focus our research in magnetic resonance images because of the absence of ionizing radiation. Although there are proposals to identify this disease in magnetic resonance images, they need an intervention from clinicians to be precise and some of them are computationally hard. In this paper we develop a novel approach to analyze magnetic resonance abdominal images and detect the lumen and the aortic wall. The method combines different algorithms in two stages to improve the detection and the segmentation so it can be applied to similar problems with other type of images or structures. In a first stage, we use a spatial fuzzy C-means algorithm with morphological image analysis to detect and segment the lumen; and subsequently, in a second stage, we apply a graph cut algorithm to segment the aortic wall. The obtained results in the analyzed images are pretty successful obtaining an average of 79% of overlapping between the automatic segmentation provided by our method and the aortic wall identified by a medical specialist. The main impact of the proposed method is that it works in a completely automatic way with a low computational cost, which is of great significance for any expert and intelligent system.