Abstract:

In recent years, popularity of both brain imaging and data visualization have significantly grown, transforming the field of neuroimaging dued to the value of actually see the brain structure and activity. The traditional approach for the study of brain has based on the exploration of individual bidimensional sections acquired by devices such as Computered Tomography, Magnetic Resonance, Positron Emission Tomography and Single Photon Emission Computerized Tomography. However, those heavy and complex images can be used for three-dimensional visualization of the brain when efficiently manipulated, usually with expensives workstations. Recent developments in the technology for advance visualization and manipulation of medical images offer new powerful resources in training contexts. This paper aims at presenting three full client-side applications for advance brain image visualization and manipulation. This work focuses on illustrate their core features and discuss their value and potential in the development of new and powerful digital resources for teaching neuroanatomy. Three advance medical image applications were selected, based on their avalaibility and scientific literature background: OsiriX®, Amira® y Analyze®. Next, core features for brain image visualization and processing were individually described for each application using original Magnetic Resonance and Computarized Tomography images previously acquired. Results include the identification and illustration of common tasks in brain imaging visualization and processing required for the development of new teaching resources for each application. The three of them allowed and advanced and efficient visualization and manipulation of brain images, including high performance, functionality, and reliability in terms of ausence of bugs or errors that usually cause crashes. Implications for educational purposes are discussed, specifically, the development of new and powerful environments for neuroanatomy teaching.

Keywords:

Technology-enhanced learning, brain image, neuroanatomy, software.