Visible Korean based on true color sectioned images for making realistic digital human, twenty years' record: a review.

Purpose: Visible Korean (VK) consists of two-dimensional (2D) images and three-dimensional (3D) models. The VK is used in various educational tools and research sources for anatomy. In this paper, we report on the records of the VK over 20 years. Methods: Research papers related to Visible Korean we...

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Publicado en:Surgical & Radiologic Anatomy Vol. 46; no. 7; pp. 935 - 948
Autores principales: Kim, Chung Yoh, Chung, Min Suk, Park, Jin Seo
Formato: Journal Article
Publicado: Springer Nature Jul2024
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jul2024
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      pub: Springer Nature
      place: New York, New York
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        atl: Visible Korean based on true color sectioned images for making realistic digital human, twenty years' record: a review.
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        au:
          Kim, Chung Yoh
          Chung, Min Suk
          Park, Jin Seo
        affil: https://ror.org/057q6n778 Department of Anatomy, Dongguk University School of Medicine, 87 Dongdae-ro, 38066, Gyeongju, Republic of Korea
      sug:
      ab: Purpose: Visible Korean (VK) consists of two-dimensional (2D) images and three-dimensional (3D) models. The VK is used in various educational tools and research sources for anatomy. In this paper, we report on the records of the VK over 20 years. Methods: Research papers related to Visible Korean were reviewed. Results: Through this report of VK records, we highlighted the essential points for making true color and ultra-high-resolution sectioned images of human and animal bodies, for making various 2D and 3D applications from the sectioned images, and for good use of the sectioned images and their applications. Conclusion: In this metaverse age that various virtual environments are required in medical education and research, the VK dataset meets the reality of virtual human models as fundamental data owing to the actual color and high resolution of the VK dataset.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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