Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive technique for assessing biochemical fingerprint of tissue composition. The need to differentiate between normal and abnormal tissues and determine type...
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Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive technique for assessing biochemical fingerprint of tissue composition. The need to differentiate between normal and abnormal tissues and determine type of abnormality before biopsy or surgery motivated development and application of MRSI. There are several technical reasons that make the brain easier than other organs to be examined with MRSI. This work presents our proposed methods and results for the analysis of the brain spectra of patients with three tumor types (malignant glioma, astrocytoma, and oligodendroglioma). After extracting features from MRSI data using wavelet and wavelet packets, we use artificial neural networks to determine the abnormal spectra and the type of abnormality. We evaluated the proposed methods using clinical and simulated MRSI data and biopsy results. The MRSI analysis results were correct 97% of the time when classifying the spectra of the clinical MRSI data into normal tissue, tumor, and radiation necrosis. They were correct 72% and 83% of the time when determining tumor types using the clinical and simulated MRSI data, respectively.
This paper proposes an audio watermark extraction technique which adopts independent component analysis (ICA) for blind watermark decoding. Unlike the existing work, our method allows to combine data synchronization a...
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This paper proposes an audio watermark extraction technique which adopts independent component analysis (ICA) for blind watermark decoding. Unlike the existing work, our method allows to combine data synchronization and watermark decoding into one optimization procedure, thus robust to transmission over different channels. Watermark encoder is designed as a nonlinear data embedding machine which is compatible to MPEG Layer 1 Model 1. It is shown that the proposed ICA based watermark decoding scheme allows decoding watermark info accurately even though the watermark to signal ratio is less than -20 dB. The method is robust to stereo-to-mono conversions and performs very well when the channel noise level is high.
We describe a novel statistical model of pressure signals that incorporates the effects of respiration on arterial (ABP) and intracranial pressure (ICP). This model can be used to synthesize pulsatile ABP and ICP sign...
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We describe a novel statistical model of pressure signals that incorporates the effects of respiration on arterial (ABP) and intracranial pressure (ICP). This model can be used to synthesize pulsatile ABP and ICP signals with similar time, frequency, and variability characteristics of real pressure signals. These synthetic signals can be used during the development, simulation, or quantitative assessment of biomedical algorithms in a variety of applications.
Heart rate variability (HRV) is frequently used to measure autonomic nervous system (ANS) activity. However, little is known about the mechanism underlying pharmacologically induced changes in HRV. Previous research h...
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Heart rate variability (HRV) is frequently used to measure autonomic nervous system (ANS) activity. However, little is known about the mechanism underlying pharmacologically induced changes in HRV. Previous research has shown that nicotine exposure stimulates the ANS, mediating a wide spectrum of physiological and behavioral effects, including altered respiratory sinus arrhythmia and enhanced arousal and attention. Using Lomb-Welch periodograms, the effect of nicotine on the ANS in 14 nicotine-naive human subjects are studied. Results showed an increase in the low frequency (LF) to high frequency (HF) ratio with little change in mean heart rate. Results suggest that nicotine affects both sympathetic and parasympathetic reactivities and that the LF/HF best characterizes early ANS activated nicotine changes in HRV. The Lomb-Welch periodogram of the HRV is also compared to the conventional interpolated Welch periodogram. The attenuation of the high frequency components due to interpolation of the non-uniform R-R intervals is found to be a function of the power of the high frequency components, increasing with increasing power. Thus analyses using Welch periodograms that make use of the high frequency components may yield erroneous results.
Recent advances in the hardware of handheld devices, opened up the way for newer applications in the healthcare sector, and more specifically, in the teleconsultation field. Out of these devices, this paper focuses on...
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Recent advances in the hardware of handheld devices, opened up the way for newer applications in the healthcare sector, and more specifically, in the teleconsultation field. Out of these devices, this paper focuses on the services that personal digital assistants and smartphones can provide to improve the speed, quality and ease of delivering a medical opinion from a distance and laying the ground for an all-wireless hospital. In that manner, PDAs were used to wirelessly support the viewing of digital imaging and communication in medicine (DICOM) images and to allow for mobile videoconferencing while within the hospital. Smartphones were also used to carry still images, multiframes and live video outside the hospital. Both of these applications aimed at increasing the mobility of the consultant while improving the healthcare service.
In this paper, a new frequency offset compensation scheme for up link of multicarrier code-division multiple access (MC-CDMA) systems is proposed. The proposed scheme exploits guard interval (GI) information embedded ...
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In InISAR system, the pixels between two ISAR images derived from corresponding antennas usually do not register properly without prior compensation. A three-dimension motion compensation method, or 3D focusing, is pu...
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CU VOCAL is a Cantonese text-to-speech (TTS) engine. We use a syllable-based concatenative synthesis approach to generate intelligible natural synthesized speech [1]. This paper describes several recent enhancements i...
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CU VOCAL is a Cantonese text-to-speech (TTS) engine. We use a syllable-based concatenative synthesis approach to generate intelligible natural synthesized speech [1]. This paper describes several recent enhancements in CU VOCAL. First, we have augmented the syllable unit selection strategy with a positional feature. This feature specifies the relative location of a syllable in a sentence serves to improve the quality of Cantonese tone realization. Second, we have developed the CU VOCAL SAPI engine, a version of the synthesizer that eases integration with applications using SAPI (Speech Application Programming Interface). We demonstrate the use of CU VOCAL SAPI in an electronic book (e-book) reader. Third, we have made an initial attempt to use the CU VOCAL SAPI engine in Web content authored with Speech Application Language Tags (SALT). The use of SALT tags can ease the task of invoking Cantonese TTS service on webpages.
Blind equalization draws a lot of attention. Several statistical objective functions such as kurtosis and constant modulus were based on the noise-free model and hence their ISI cancellers were sensitive to noise. In ...
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