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[From digital virtual human, three-dimensional visualization to digital intelligence in liver surgery].

C H Fang1, P Zhang1, Y Y Lau2

  • 1First Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University; Guangdong Provincial Clinical and Engineering Center of Digital Medicine, Guangzhou 510282, China.

Zhonghua Wai Ke Za Zhi [Chinese Journal of Surgery]
|January 7, 2020
PubMed
Summary
This summary is machine-generated.

Digital intelligent hepatobiliary surgery advances through innovations in 3D visualization, deep learning, and real-time imaging. Future developments aim for molecular-level tumor definition and AI-guided robotic surgery for improved liver cancer outcomes.

Keywords:
Digital intelligenceDigital virtual humanHepatectomyImaging, three-dimensionalNavigationThree dimensional visualization

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Area of Science:

  • Digital and intelligent surgical technologies
  • Hepatobiliary surgery advancements
  • Medical imaging and artificial intelligence

Background:

  • Digital intelligent hepatobiliary surgery has evolved significantly over decades.
  • Progress includes virtual human technology, 3D visualization systems, and clinical integration of digital tools.
  • The field has shifted from empirical methods to data-driven approaches like deep learning and advanced imaging.

Purpose of the Study:

  • To review the evolution of digital intelligent hepatobiliary surgery.
  • To highlight key technological advancements and their impact on diagnosis and treatment.
  • To discuss future directions and their clinical significance in liver cancer management.

Main Methods:

  • Review of technological evolution in digital hepatobiliary surgery.
  • Analysis of advancements from 3D visualization to AI-driven diagnostics and real-time image guidance.
  • Exploration of molecular imaging and robotic navigation systems.

Main Results:

  • Digital surgery has progressed from basic visualization to intelligent diagnosis and treatment models.
  • Innovations include deep learning for disease diagnosis and multi-modal image guidance for surgery.
  • Future potential lies in molecular-level tumor boundary definition and AI-assisted robotic hepatectomy.

Conclusions:

  • Continuous innovation is vital for the advancement of digital intelligent hepatobiliary surgery.
  • Molecular-level diagnosis and AI-driven robotic surgery hold promise for improving liver cancer prognosis.
  • Developing intelligent navigation systems for hepatectomy presents significant clinical opportunities.