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- ÍtemReducción de Ruido en Señales de Espectroscopia en Resonancia Magnética con Transformada Wavelets COINFLET Y BIORTHOGONAL(Fundación Universitaria Los Libertadores. Sede Bogotá., ) Navarrete Forero, Fabio Andrés; Cancino del Greiff, Héctor FernandoThis document presents the application of the Coinflet Wavelet Transform and the Biorthogonal wavelet family to reduce noise in magnetic resonance images, used in non-invasive medical processes. Noisy measured signals are processed by a noise cleaning algorithm in Matlab; then the signals are converted to the frequency domain where they are processed Compressed and cleaned from Noisy source. The wavelet transform is a technique used to manipulate, analyze, and compress signals more efficiently in magnetic resonance imaging (MRI) noise reduction applications, which can often be affected by Gaussian noise from from different sources, said Gaussian noise is difficult to clean due to the amount of information that must be processed in diagnoses of ligament ruptures to tumors. The Coiflet wavelet uses compact support techniques and improved regularity properties to capture fine details in the image and preserve structural features. relevant, while reducing unwanted noise. In contrast, the Biorthogonales family of wavelets have the advantage of having separable analysis and synthesis filters, which simplifies the filtering process and improves efficiency. The noise reduction with wavelet presented satisfactory results at high frequencies where the Coinflet wavelet stood out in comparison to the Daubechies and the Biorthogonal using the Penallo Threshold technique.
- ÍtemReducción de ruido de señales de resonancia magnética con método wavelet, biortogonal (RBIO) y MEYER (DMEY).(Fundación Universitaria Los Libertadores. Sede Bogotá., ) Vivas Ramos, Fabian Alejandro; Cancino de Greif, Héctor FernandoIn the development of the study or taking of images in the diagnosis of cases or health problems, it plays a fundamental role for the detection and prevention of diseases. In fact, this system is mainly used as diagnostic support. The analysis from MRI (Magnetic Resonance Imaging) images allows organs such as the brain, spinal cord, nerves, muscles, ligaments, tendons, tumors or cysts in the liver; appear clearer in contrast to X-rays and CT) [1]. However, storing and transmitting this type of images through the network implies increasing the bandwidth and reducing the transmission speed, since digital images can present three types of redundancy: psychovisual, spatial, and encoding. From this arises the need to apply compression methods, without loss, which reduce the bit rate for transmission or storage and preserve the relevant information without affecting the quality of the compressed image; factors that are fundamental in the hospital and telemedicine environment. One of the techniques applied to compress, without losses, is the Wavelet transform (WT) proposed at the end of the 80s; This provides simultaneous information on the amplitude and frequency of the signals from the translation and scale change of a function called: Mother Wavelet, which gives rise to 5 different Wavelet families, among which are: Haar, Daubechies, Biortogonal, Symlet. , Meyer, Coiflets, Mexican Hat, Shannon, and Morlet [2]. In addition, it has characteristics such as: orthogonality, invertibility, multiscalar representation, compaction and energy invariance [3]. These characteristics constitute the main difference with respect to compression methods such as the Fourier transform and the DCT (Discrete Cosine Transform), where only frequency information of the signal is obtained, that is, the maximum spectral resolution is achieved sacrificing temporal resolution. [4]. For this reason, WT is currently one of the most powerful tools in signal processing and compression of MRI images. Generally, in lossless compression techniques, the DWT (Discrete Wavelet Transform) is used because it decomposes the images by: low-pass-low-pass (LL), low-pass-high-pass (LH), high-pass filter -low pass (HL) and high pass high pass (HH). The LL filter generates a rough coefficient and the remaining three are verbose coefficients. The LL sub-band contains information of the low frequencies of the original image. In a similar way, the bands, HL, LH and HH, contain information of the high frequencies, this allows to apply the reconstruction process after decimating said coefficients and with it, to Apply compression processes without useful losses to reduce the bandwidth, improve the storage capacity and increase the transmission speed without affecting the quality of the diagnostic image, based on this, it seeks to reduce the noise of the magnetic resonance using, The method of the discrete Biorthogonal wavelets transform (rbio) and discrete Meyer (Dmeyer ).
- ÍtemReducción de ruido de señales de resonancia magnética con método wavelet, Biortogonal (RBIO) y Meyer (DMEY)(Fundación Universitaria Los Libertadores. Sede Bogotá., ) Vivas Ramos, Fabian Alejandro; Cansino, FernandoIn the development of the study or imaging in the diagnosis of cases or health problems, it plays a fundamental role in the detection and prevention of diseases. In fact, this system is mainly used as a diagnostic support. The analysis from MRI (Magnetic Resonance Imaging) images allows organs such as the brain, spinal cord, nerves, muscles, ligaments, tendons, tumors or cysts in the liver to be seen more clearly in contrast to X-rays and CT) [1]. However, storing and transmitting this type of images through the network implies increasing the bandwidth and decreasing the transmission speed, due to the fact that digital images can present three types of redundancy: psychovisual, spatial and coding. From this arises the need to apply compression methods, without loss, that reduce the rate of transmission. lossless compression methods that reduce the bit rate for transmission or storage and preserve the relevant information without affecting the quality of the compressed image; factors that are essential in the hospital and Telemedicine field.
- ÍtemReducción de ruido en señales de espectroscopia en resonancia magnética con transformada wavelets COINFLET y BIORTHOGONAL(Fundación Universitaria Los Libertadores. Sede Bogotá., ) Navarrete Forero, Fabio Andres; Cancino del Greiff, Héctor FernandoThis paper presents the application of the Coinflet Wavelet Transform and the Biorthogonal wavelet family for noise reduction in magnetic resonance images used in non-invasive medical processes. The measured signals with noise are processed by a noise cleaning algorithm in Matlab; then the signals are converted to the frequency domain where they are processed Compressed and cleaned from Noisy source. The wavelet transform is a technique used to manipulate, analyze and compress signals more efficiently in magnetic resonance imaging (MRI) noise reduction applications, which can often be affected by Gaussian noise from different sources, such Gaussian noise is difficult to clean because of the amount of information to be processed in diagnostics from ligament ruptures to tumors.
- ÍtemOptimización de antena de ancho de banda ultra amplio (uwb) tipo conica con corrugaciones(Fundación Universitaria Los Libertadores. Sede Bogotá., ) Monroy Rozo, Edwin Fernando; Patalagua Bernal, Luis Enrique; Nova Manosalva, Omar ArielThe purpose of this project lies in; design, calculate, simulate and validate the operation of a corrugation type UWB (Ultra-Wide Band) antenna, optimizing the operating frequencies by varying the geometry for better performance in the bandwidth. The proposed design of the rectangular and cone type antennas by means of the method used of rectangular forms of exponential order and ground plane to design a compact size omnidirectional antenna with a series of inserts or corrugation type elements established directly in the patch, make the distribution of the induced magnetic field is more efficient, allowing us to obtain greater frequency coverage. The simulated and measured results show that using this method the bandwidth improves by 3.23% over the percentage improvement already achieved in the cone type antenna.