Implementación de una plataforma web para la visualización y manipulación de ecografías intravasculares

Abstract

[en] In order to increase the precision of contour computation, this bachelor’s thesis proposes an application for the administration of intravascular ultrasounds. A noninvasive imaging diagnostic method used to assess vascular disorders is intravascular ultrasounds. Making significant clinical decisions requires accurate handling of the findings. The application is created in Django using the Python programming language, with cloud file storage provided by Google Cloud Storage, and being deployed in Azure App Service. The instrument seeks to increase the effectiveness of intravascular ultrasound administration and provide more accurate findings to support interpretation and diagnosis through the functionalities developed during the project. Among them and the most important in this work has been the ability to be able to draw the middle and intimate tunic of a layer of an intravascular ultrasound. In addition, the incorporation of another project has been achieved, which uses machine learning techniques to calculate contours in intravascular ecographs. This additional functionality has further improved the accuracy and analytical capability of the instrument, allowing for more detailed interpretation and a more reliable diagnosis.