Procesamiento de Señales e Imágenes Digitales
URI permanente para esta colecciónhttp://54.81.141.168/handle/123456789/31440
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Ítem Texto completo enlazado Robust Minimmun Variance Beamformer using Phase Aberration Correction Methods(Pontificia Universidad Católica del Perú, 2017-04-28) Chau Loo Kung, Gustavo Ramón; Lavarello Montero, Roberto Janniel; Dahl, Jeremy J.The minimum variance (MV) beamformer is an adaptive beamforming method that has the potential to enhance the resolution and contrast of ultrasound images. Although the sensitivity of the MV beamformer to steering vector errors and array calibration errors is well-documented in other fields, in ultrasound it has been tested only under gross sound speed errors. Several robust MV beamformers have been proposed, but have mainly reported robustness only in the presence of sound speed mismatches. Additionally the impact of PAC methods in mitigating the effects of phase aberration in MV beamformed images has not been observed Accordingly, this thesis report consists on two parts. On the first part, a more complete analysis of the effects of different types of aberrators on conventional MV beamforming and on a robust MV beamformer from the literature (Eigenspace-based Minimum Variance (ESMV) beamformer) is carried out, and the effects of three PAC algorithms and their impact on the performance of the MV beamformer are analyzed (MV-PC). The comparison is carried out on Field II simulations and phantom experiments with electronic aberration and tissue aberrators. We conclude that the sensitivity to speed of sound errors and aberration limit the use of the MV beamformer in clinical applications, and that the effect of aberration is stronger than previously reported in the literature. Additionally it is shown that under moderate and strong aberrating conditions, MV-PC is a preferable option to ESMV. On the second part, we propose a new, locally-adaptive, phase aberration correction method (LAPAC) able to improve both DAS and MV beamformers that integrates aberration correction for each point in the image domain into the formulation of the MV beamformer. The new method is tested using fullwave simulations of models of human abdominal wall, experiments with tissue aberrators, and in vivo carotid images. The LAPAC method is compared with conventional phase aberration correction with delay-and-sum beamforming (DAS-PC) and MV-PC. The proposed method showed between 1-4 dB higher contrast than DAS-PC and MV-PC in all cases, and LAPAC-MV showed better performance than LAPAC-DAS. We conclude that LAPAC may be a viable option to enhance ultrasound image quality of both DAS and MV in the presence of clinically-relevant aberrating conditions.Ítem Texto completo enlazado 3D reconstruction of chronic wounds using a hand-held camcorder and its application in cutaneous leishmaniasis wounds(Pontificia Universidad Católica del Perú, 2017-03-09) Casas Guido, Eda Leslie Mónica; Castañeda Aphan, BenjamínChronic wounds are a major healthcare problem worldwide which mainly a ects geriatric population and patients with limited mobility. In tropical countries, Cutaneous Leishmaniasis (CL) is also a cause for chronic wounds, being endemic in 75% of Peru . In this context, the assessment of these type of wounds represents a big challenge due to the limited access to specialized medical resources. This work aims to develop a video-based method to compute the 3D point cloud of skin wounds which could provide accurate metrics for medical assessment despite of the location of the patient. Recently, CL specialists have used metrics as volume in clinical assessment with promising results. The acquisition protocol is prompt to be user friendly and feasible in remote locations; the video is taken using a commercial hand-held video camera without a rig or special illumination. The algorithm follows the Structure from Motion methodology: FAST feature detector, pyramidal optical flow and Jacob’s method for missing points estimation. The results show good performance in terms of accuracy and repeatability of the point cloud computation, less than 0.6 mm and 0.21 mm respectively. However, experiments suggest that the volume computation technique does not adapt well to the proposed method output and requires a deeper analysis. The method has been entirely implemented using open source libraries.