Fused Visualization and Feature Highlighting to Assist Depth Recognition in Transparent Stereoscopic Visualization

Autor: Yuichi Sakano, Satoshi Tanaka, Miwa Miyawaki, Daimon Aoi, Hiroshi Ando, Liang Li, Roberto Lopez-Gulliver, Kyoko Hasegawa
Rok vydání: 2019
Předmět:
Zdroj: Innovation in Medicine and Healthcare Systems, and Multimedia ISBN: 9789811385650
DOI: 10.1007/978-981-13-8566-7_19
Popis: In the medical field, computer graphics (CG) is used to visualize the internal structure of the human body, which is important in diagnosis and surgical planning. Transparent visualization, on the other hand, visualizes the whole image and the inside at the same time, enables intuitive structure grasping, and is useful for three-dimensional visualization in the medical field. However, in transparent stereoscopy, the problem that the depth is underestimated rather than the actual object has been confirmed from the previous research. Therefore, in this study, we extract the surface of the volume data as a surface, overlap it with the original semitransparent volume to give a role as a silhouette, and make it a new clue to solve the problems of transparent stereopsis. Then, an evaluation experiment was conducted on the depth grasp of the medical images to which the proposed method was applied. The result shows that the depth was overestimated over the correct value under a plurality of conditions, and by fusing the surfaces, the surface to be compared was perceived more deeply. Regarding the feature highlighting, under specific conditions, it was perceived farther in the back.
Databáze: OpenAIRE