Development and evaluation of an integrated image-guided robotic system for hair transplant surgery

IF 4.4 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Rattapon Thuangtong, Ornpreeya Anantawilailekha, Ponchita Prasertsin, Jackrit Suthakorn
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Abstract

This study presented the development and evaluation of an integrated image-guided robotic system for hair transplant surgery. A novel surgical robot was designed, incorporating an image-guided system, a dual-function needle mechanism, and a comprehensive robotic system capable of performing both follicle harvesting and implantation in a unified setup. The robot comprised three main subsystems: the image-guidance system, the dual-function needle, and the robotic hardware. Each subsystem was meticulously developed and individually described, detailing the specific processes and mechanisms involved. Experimentation involved a silicone phantom embedded with filaments to mimic real human hair density, providing a realistic simulation for testing. The image-guided system demonstrated high precision in detecting the positions of hair follicles, achieving an accuracy rate of 89 %. Meanwhile, the dual-function needle proved effective in executing both the harvesting and implanting functions, achieving harvest and implant success rates of 83.3 % and 53.3 %, respectively. It was important to note, however, that the suction system integrated into the needle mechanism did not function as intended. Further simulations conducted on the robotic system affirmed its suitability for a wide range of head sizes, specifically those with a breadth diameter between 113 and 179 mm, effectively encompassing most of the Asian demographic. This integration of advanced robotics and image-guidance aimed to enhance the efficacy and precision of hair transplant procedures.
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来源期刊
Computational and structural biotechnology journal
Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
9.30
自引率
3.30%
发文量
540
审稿时长
6 weeks
期刊介绍: Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology
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