El objetivo del trabajo que se presenta es la identificación de innovaciones y nuevos procesos en carnaza como subproducto de la curtición. Para esto se realizó un proceso de vigilancia tecnológica a través de una búsqueda de información, referente a juguetes caninos, tecnologías de proceso, normatividad, y tendencias. Se aplicó la metodología de análisis del ciclo de vida de la tecnología a través de curvas en S. Entre los documentos más importantes se encontraron dos nuevos procesos de elaboración para la fabricación de juguetes caninos descritos en dos patentes de Estados Unidos. Además, para la harina de carnaza su punto de inflexión en artículos se presentó en el periodo 2016-2018 lo cual representa una oportunidad para continuar investigando sobre esta tecnología.
The success of stereotactic surgery for Deep Brain Stimulation depends critically on the exact positioning of a microelectrode recording in a target area of the brain. This paper presents the software system NEUROZONE composed of two main applications: first, it allows online recognition of brain structures by the analysis of signals from microelectrode recordings (MER), and second, it processes and analyses off-line databases allowing the inclusion of new trained classifiers for automatic identification. The software serves as a support to the analysis done by a medical specialist during surgery, and seeks to reduce the adverse side effects that may occur because of inadequate identification of the target areas. The software also allows the specialists to label recordings obtained during surgery, in order to generate a new off-line database or increase the amount of records in an already existing off-line database. NEUROZONE has been tested for Deep Brain Stimulation performed at the Institute for Epilepsy and Parkinson of the Eje Cafetero (Colombia), achieving positive identifications of the Subthalamic Nucleus (STN) over to 85% using a naive Bayes classifier.
RESUMENEl registro es una de las tareas más importantes dentro del procesamiento de imágenes, consiste en encontrar una transformación geométrica que relacione los puntos de una imagen y otra con el fin de corregir las diferencias de tamaño, posición, orientación o distorsión espacial que pueda presentarse, de manera que sea posible una comparación directa entre ellas que facilite el análisis por parte del especialista, ya sea para el diagnóstico de una enfermedad o para la planeación de una cirugía extereotáxica. En los últimos años se han propuesto técnicas de registro multimodal, especialmente entre imágenes CT (Tomografía computarizada) y MRI (Resonancia magnética), sin embargo, algunos de los problemas que aún se presentan permanecen sin resolver, y por ello son un campo activo de investigación. Debido a los problemas de exactitud que presentan los modelos de registro rígidos y no rígidos unimodales, los cuales aún no alcanzan la precisión necesaria para aplicaciones de neurocirugía y la necesidad de contar con herramientas de neuronavegación para el apoyo en la planeamiento de cirugías derivadas de procesos de neurocirugía, este artículo propone el desarrollo de una herramienta para el registro de estructuras cerebrales 3d utilizando técnicas de procesamiento de imágenes. Los resultados evidencian que una herramienta de registro permite emparejar un determinado atlas cerebral a un registro histológico de un determinado paciente, además que del sistema desarrollado permite su ejecución en línea lo cual beneficia la funcionalidad del sistema en procesos de neurocirugía. ABSTRACTMedical image registration is one of the most important tasks in image guide surgery. It consists of finding a geometrical transformation that relates the points of images in order to correct for differences in size, position, orientation or spatial distortion that can occur, so it is possible a direct comparison between them to facilitate analysis by the specialist, either for diagnosis of a disease or for planning a stereotaxic surgery. In recent years multimodal registration techniques have been proposed, especially among images CT (computed tomography) and MRI (Magnetic Resonance Imaging). However, some problems still remain unsolved, and are therefore an active field of research. Due to problems of accuracy in models of rigid and non-rigid registration , which have not yet reached the precision required for neurosurgical applications, this article proposes the development of a tool for 3D brain registration using image processing techniques . The results show that a registration tool allows matching a given brain histological atlas of a particular patient. Besides, the developed system can be executed online, which benefits system functionality in neurosurgery procedures.
Deep brain stimulation (DBS) is the most suitable surgical procedure for patients with Parkinson disease whose symptoms are not well controlled by drug treatment, or who cannot tolerate the side-effects of medication. The success of this surgery procedure, depends on the correct location of the neurostimulator device over the basal ganglia area (i.e. thalamus and globus pallidus). This paper presents a software system DEEPBRAINnav as support tool in Parkinson surgery. This software serves as support to the neurological specialist in DBS surgery. DEEPBRAINnav is composed mainly by two applications. First, it allows to the medical specialist, online recognition of brain structures by the analysis of signals from microelectrode recordings (MER), as well as analyses offline databases allowing the inclusion of new trained classifiers for automatic identification of thalamus location. Secondly, the software includes an interactive application to perform the tracking of the microelectrode device, allowing to the neurosurgeon visualize the path and real location of the microelectrode device implant process. DEEPBRAINnav has been tested for Deep Brain Stimulation surgeries performed at the Institute for Epilepsy and Parkinson of the Eje Cafetero (Colombia). The results shows an accurate tracking of the microelectrode implanting process and achieving positive identifications of the Subthalamic Nucleus (STN) over to 85% using a naive Bayes classifier. Furthermore, develop applications for image and signals guide surgery procedures, allows to the neurologist obtain more support information of a surgery procedure given, with the aim to increase the robustness of the DBS surgery.
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