Methods of creating digital twins of medico-biological objects using otolaryngology as an example

The paper presents an in-depth analysis on the most suitable tools and techniques for the formulation of a digital twin, specifically focusing on internal organs. The larynx, a pivotal organ in the human respiratory and vocal systems, is highlighted as the primary case study. The basis of this digital twin generation is the video stream sourced directly from a medical device's onboard camera, which provides real-time visual data of the organ. Two methodologies are put under the microscope in this study: one that harnesses the power of neural networks and another grounded in algorithmic reconstruction using crucial points or markers within the video feed. Each method is evaluated against a set of well-defined criteria. These benchmarks include the efficiency of the tool, the accuracy of the digital representation it produces, the speed of its response, and its overall ap-plicability within the confines of a typical medical environment. After a rigorous comparative analysis, the research gravitates towards neural network-based approaches, spotlighting them due to several standout features. Neural networks, as elucidated in the paper, exhibit remarkable adaptability, ensuring that they can be tailored to diverse medical scenarios. Their accuracy, even when confronted with "noisy" or fragmented data, is another standout feature. This is paramount, especially in real-world scenarios where the data might not always be pristine. The ability of neural networks to sieve through such data and still produce ac-curate digital representations is a significant advancement in the field. In conclusion, by affirming the superior potential of neural networks in crafting precise digi-tal avatars of internal organs, the research not only provides a blueprint for enhanced diagnostic and therapeutic methodologies but also underscores a paradigm shift in how medical professionals can leverage technology for better patient outcomes. This synthesis of medical expertise and cut-ting-edge technology is poised to redefine the boundaries of medical science, heralding a new era of advanced diagnostics and treatment modalities.

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Publication Details

Journal
System technologies
Published
2024-10-03
DOI
https://doi.org/10.34185/1562-9945-5-154-2024-14
Primary Topic
Medical and Biological Sciences
Type
article
Field-Weighted Citation Impact
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article

Methods of creating digital twins of medico-biological objects using otolaryngology as an example

Vladyslav Peschanskii, Yevgeniya Sulema
System technologies
Medical and Biological Sciences
article

Methods of creating digital twins of medico-biological objects using otolaryngology as an example

Vladyslav Peschanskii, Yevgeniya Sulema
article en

Abstract

The paper presents an in-depth analysis on the most suitable tools and techniques for the formulation of a digital twin, specifically focusing on internal organs. The larynx, a pivotal organ in the human respiratory and vocal systems, is highlighted as the primary case study. The basis of this digital twin generation is the video stream sourced directly from a medical device's onboard camera, which provides real-time visual data of the organ. Two methodologies are put under the microscope in this study: one that harnesses the power of neural networks and another grounded in algorithmic reconstruction using crucial points or markers within the video feed. Each method is evaluated against a set of well-defined criteria. These benchmarks include the efficiency of the tool, the accuracy of the digital representation it produces, the speed of its response, and its overall ap-plicability within the confines of a typical medical environment. After a rigorous comparative analysis, the research gravitates towards neural network-based approaches, spotlighting them due to several standout features. Neural networks, as elucidated in the paper, exhibit remarkable adaptability, ensuring that they can be tailored to diverse medical scenarios. Their accuracy, even when confronted with "noisy" or fragmented data, is another standout feature. This is paramount, especially in real-world scenarios where the data might not always be pristine. The ability of neural networks to sieve through such data and still produce ac-curate digital representations is a significant advancement in the field. In conclusion, by affirming the superior potential of neural networks in crafting precise digi-tal avatars of internal organs, the research not only provides a blueprint for enhanced diagnostic and therapeutic methodologies but also underscores a paradigm shift in how medical professionals can leverage technology for better patient outcomes. This synthesis of medical expertise and cut-ting-edge technology is poised to redefine the boundaries of medical science, heralding a new era of advanced diagnostics and treatment modalities.

System technologiesVol. 5(154)
Openalex Percentile: Top 61%
Medical and Biological Sciences
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Methods of creating digital twins of medico-biological objects using otolaryngology as an example — Vladyslav Peschanskii, Yevgeniya Sulema · System technologies (2024) | TGRS Research Map | TGRS