Examinando por Autor "Vivas Ramos, Fabian Alejandro"
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- 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 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 ).