Literature DB >> 22434672

Experimental evidence for improved neuroimaging interpretation using three-dimensional graphic models.

Pablo Ruisoto1, Juan Antonio Juanes, Israel Contador, Paula Mayoral, Alberto Prats-Galino.   

Abstract

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 visualization has not yet been assessed systematically. This report analyzes whether 3D volumetric 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 experimental 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 analyzed. 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 comparison 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.
Copyright © 2012 American Association of Anatomists.

Entities:  

Mesh:

Year:  2012        PMID: 22434672     DOI: 10.1002/ase.1275

Source DB:  PubMed          Journal:  Anat Sci Educ        ISSN: 1935-9772            Impact factor:   5.958


  13 in total

1.  Computer-Based Visualization System for the Study of Deep Brain Structures Involved in Parkinson's Disease.

Authors:  Juan A Juanes; Pablo Ruisoto; José A Obeso; Alberto Prats; Joan San-Molina
Journal:  J Med Syst       Date:  2015-09-14       Impact factor: 4.460

2.  Interactive 3D-PDF Presentations for the Simulation and Quantification of Extended Endoscopic Endonasal Surgical Approaches.

Authors:  Marija Mavar-Haramija; Alberto Prats-Galino; Juan A Juanes Méndez; Anna Puigdelívoll-Sánchez; Matteo de Notaris
Journal:  J Med Syst       Date:  2015-08-26       Impact factor: 4.460

3.  Computer Applications in Health Science Education.

Authors:  Juan A Juanes; Pablo Ruisoto
Journal:  J Med Syst       Date:  2015-08-08       Impact factor: 4.460

4.  Computer-Based Learning: Graphical Integration of Whole and Sectional Neuroanatomy Improves Long-Term Retention.

Authors:  Farah Naaz; Julia H Chariker; John R Pani
Journal:  Cogn Instr       Date:  2014

5.  New Generation of Three-Dimensional Tools to Learn Anatomy.

Authors:  Roberto D Tabernero Rico; Juan A Juanes Méndez; Alberto Prats Galino
Journal:  J Med Syst       Date:  2017-04-12       Impact factor: 4.460

6.  Morphological and Volumetric Assessment of Cerebral Ventricular System with 3D Slicer Software.

Authors:  Miguel Gonzalo Domínguez; Cristina Hernández; Pablo Ruisoto; Juan A Juanes; Alberto Prats; Tomás Hernández
Journal:  J Med Syst       Date:  2016-05-05       Impact factor: 4.460

7.  Computer-based learning: interleaving whole and sectional representation of neuroanatomy.

Authors:  John R Pani; Julia H Chariker; Farah Naaz
Journal:  Anat Sci Educ       Date:  2012-07-03       Impact factor: 5.958

8.  NOWinBRAIN: a Large, Systematic, and Extendable Repository of 3D Reconstructed Images of a Living Human Brain Cum Head and Neck.

Authors:  Wieslaw L Nowinski
Journal:  J Digit Imaging       Date:  2022-01-10       Impact factor: 4.056

9.  Photogrammetry of Human Specimens: An Innovation in Anatomy Education.

Authors:  Aldis H Petriceks; Ashley S Peterson; Miguel Angeles; W Paul Brown; Sakti Srivastava
Journal:  J Med Educ Curric Dev       Date:  2018-09-17

Review 10.  Two-step verification of brain tumor segmentation using watershed-matching algorithm.

Authors:  Mohiudding Ahmad; S M Kamrul Hasan
Journal:  Brain Inform       Date:  2018-08-14
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.