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Titre
Experimental evidence for improved neuroimaging interpretation using three‐dimensional graphic models
Autor(es)
Sujet
Neuroanatomy education
Gross anatomy education
Medical education
Brain
Neuroimaging
Volumetric visualization
Visual-spatial abilities
2D/3D testing
Learning
Clasificación UNESCO
2410.02 Anatomía Humana
Fecha de publicación
2012
Resumen
[EN]Three-dimensional (3D) or volumetric visualization is a useful resource for learning
about the anatomy of the human brain. However, the effectiveness of 3D spatial visual ization has not yet been assessed systematically. This report analyzes whether 3D volu metric visualization helps learners to identify and locate subcortical structures more
precisely than classical cross-sectional images based on a two dimensional (2D)
approach. Eighty participants were assigned to each experimental condition: 2D cross sectional visualization vs. 3D volumetric visualization. Both groups were matched for
age, gender, visual-spatial ability, and previous knowledge of neuroanatomy. Accuracy
in identifying brain structures, execution time, and level of confidence in the response
were taken as outcome measures. Moreover, interactive effects between the experimen tal conditions (2D vs. 3D) and factors such as level of competence (novice vs. expert),
image modality (morphological and functional), and difficulty of the structures were an alyzed. The percentage of correct answers (hit rate) and level of confidence in responses
were significantly higher in the 3D visualization condition than in the 2D. In addition,
the response time was significantly lower for the 3D visualization condition in compari son with the 2D. The interaction between the experimental condition (2D vs. 3D) and
difficulty was significant, and the 3D condition facilitated the location of difficult
images more than the 2D condition. 3D volumetric visualization helps to identify brain
structures such as the hippocampus and amygdala, more accurately and rapidly than
conventional 2D visualization. This paper discusses the implications of these results
with regards to the learning process involved in neuroimaging interpretation.
URI
ISSN
1935-9772
DOI
10.1002/ase.1275
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