Metaverse and Medical Diagnosis: A Blockchain-Based Digital Twinning Approach Based on MobileNetV2 Algorithm for Cervical Vertebral Maturation
Advanced mathematical and deep learning (DL) algorithms have recently played a crucial role in diagnosing medical parameters and diseases. One of these areas that need to be more focused on is dentistry. This is why creating digital twins of dental issues in the metaverse is a practical and effectiv...
| Główni autorzy: | , , , , , , |
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| Format: | Artykuł |
| Język: | English |
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MDPI AG
2023-04-01
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| Seria: | Diagnostics |
| Hasła przedmiotowe: | |
| Dostęp online: | https://www.mdpi.com/2075-4418/13/8/1485 |
| _version_ | 1827745307663794176 |
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| author | Omid Moztarzadeh Mohammad (Behdad) Jamshidi Saleh Sargolzaei Fatemeh Keikhaee Alireza Jamshidi Shabnam Shadroo Lukas Hauer |
| author_facet | Omid Moztarzadeh Mohammad (Behdad) Jamshidi Saleh Sargolzaei Fatemeh Keikhaee Alireza Jamshidi Shabnam Shadroo Lukas Hauer |
| author_sort | Omid Moztarzadeh |
| collection | DOAJ |
| description | Advanced mathematical and deep learning (DL) algorithms have recently played a crucial role in diagnosing medical parameters and diseases. One of these areas that need to be more focused on is dentistry. This is why creating digital twins of dental issues in the metaverse is a practical and effective technique to benefit from the immersive characteristics of this technology and adapt the real world of dentistry to the virtual world. These technologies can create virtual facilities and environments for patients, physicians, and researchers to access a variety of medical services. Experiencing an immersive interaction between doctors and patients can be another considerable advantage of these technologies, which can dramatically improve the efficiency of the healthcare system. In addition, offering these amenities through a blockchain system enhances reliability, safety, openness, and the ability to trace data exchange. It also brings about cost savings through improved efficiencies. In this paper, a digital twin of cervical vertebral maturation (CVM), which is a critical factor in a wide range of dental surgery, within a blockchain-based metaverse platform is designed and implemented. A DL method has been used to create an automated diagnosis process for the upcoming CVM images in the proposed platform. This method includes MobileNetV2, a mobile architecture that improves the performance of mobile models in multiple tasks and benchmarks. The proposed technique of digital twinning is simple, fast, and suitable for physicians and medical specialists, as well as for adapting to the Internet of Medical Things (IoMT) due to its low latency and computing costs. One of the important contributions of the current study is to use of DL-based computer vision as a real-time measurement method so that the proposed digital twin does not require additional sensors. Furthermore, a comprehensive conceptual framework for creating digital twins of CVM based on MobileNetV2 within a blockchain ecosystem has been designed and implemented, showing the applicability and suitability of the introduced approach. The high performance of the proposed model on a collected small dataset demonstrates that low-cost deep learning can be used for diagnosis, anomaly detection, better design, and many more applications of the upcoming digital representations. In addition, this study shows how digital twins can be performed and developed for dental issues with the lowest hardware infrastructures, reducing the costs of diagnosis and treatment for patients. |
| first_indexed | 2024-03-11T05:06:14Z |
| format | Article |
| id | doaj.art-910e08901b69478c8f9b3905e9654eb0 |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-11T05:06:14Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-910e08901b69478c8f9b3905e9654eb02023-11-17T18:55:45ZengMDPI AGDiagnostics2075-44182023-04-01138148510.3390/diagnostics13081485Metaverse and Medical Diagnosis: A Blockchain-Based Digital Twinning Approach Based on MobileNetV2 Algorithm for Cervical Vertebral MaturationOmid Moztarzadeh0Mohammad (Behdad) Jamshidi1Saleh Sargolzaei2Fatemeh Keikhaee3Alireza Jamshidi4Shabnam Shadroo5Lukas Hauer6Department of Stomatology, University Hospital Pilsen, Faculty of Medicine in Pilsen, Charles University, 323 00 Pilsen, Czech RepublicFaculty of Electrical Engineering, University of West Bohemia, Univerzitní 22, 306 14 Pilsen, Czech RepublicDepartment of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad 9187147578, IranDepartment of Orthodontics, Faculty of Dentistry, Zahedan University of Medical Sciences, Zahedan 9816743463, IranDentistry School, Babol University of Medical Sciences, Babol 4717647745, IranDepartment of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad 9187147578, IranDepartment of Stomatology, University Hospital Pilsen, Faculty of Medicine in Pilsen, Charles University, 323 00 Pilsen, Czech RepublicAdvanced mathematical and deep learning (DL) algorithms have recently played a crucial role in diagnosing medical parameters and diseases. One of these areas that need to be more focused on is dentistry. This is why creating digital twins of dental issues in the metaverse is a practical and effective technique to benefit from the immersive characteristics of this technology and adapt the real world of dentistry to the virtual world. These technologies can create virtual facilities and environments for patients, physicians, and researchers to access a variety of medical services. Experiencing an immersive interaction between doctors and patients can be another considerable advantage of these technologies, which can dramatically improve the efficiency of the healthcare system. In addition, offering these amenities through a blockchain system enhances reliability, safety, openness, and the ability to trace data exchange. It also brings about cost savings through improved efficiencies. In this paper, a digital twin of cervical vertebral maturation (CVM), which is a critical factor in a wide range of dental surgery, within a blockchain-based metaverse platform is designed and implemented. A DL method has been used to create an automated diagnosis process for the upcoming CVM images in the proposed platform. This method includes MobileNetV2, a mobile architecture that improves the performance of mobile models in multiple tasks and benchmarks. The proposed technique of digital twinning is simple, fast, and suitable for physicians and medical specialists, as well as for adapting to the Internet of Medical Things (IoMT) due to its low latency and computing costs. One of the important contributions of the current study is to use of DL-based computer vision as a real-time measurement method so that the proposed digital twin does not require additional sensors. Furthermore, a comprehensive conceptual framework for creating digital twins of CVM based on MobileNetV2 within a blockchain ecosystem has been designed and implemented, showing the applicability and suitability of the introduced approach. The high performance of the proposed model on a collected small dataset demonstrates that low-cost deep learning can be used for diagnosis, anomaly detection, better design, and many more applications of the upcoming digital representations. In addition, this study shows how digital twins can be performed and developed for dental issues with the lowest hardware infrastructures, reducing the costs of diagnosis and treatment for patients.https://www.mdpi.com/2075-4418/13/8/1485dental surgerydentistrydigital twinsdeep learningCNNadvanced mathematical models |
| spellingShingle | Omid Moztarzadeh Mohammad (Behdad) Jamshidi Saleh Sargolzaei Fatemeh Keikhaee Alireza Jamshidi Shabnam Shadroo Lukas Hauer Metaverse and Medical Diagnosis: A Blockchain-Based Digital Twinning Approach Based on MobileNetV2 Algorithm for Cervical Vertebral Maturation Diagnostics dental surgery dentistry digital twins deep learning CNN advanced mathematical models |
| title | Metaverse and Medical Diagnosis: A Blockchain-Based Digital Twinning Approach Based on MobileNetV2 Algorithm for Cervical Vertebral Maturation |
| title_full | Metaverse and Medical Diagnosis: A Blockchain-Based Digital Twinning Approach Based on MobileNetV2 Algorithm for Cervical Vertebral Maturation |
| title_fullStr | Metaverse and Medical Diagnosis: A Blockchain-Based Digital Twinning Approach Based on MobileNetV2 Algorithm for Cervical Vertebral Maturation |
| title_full_unstemmed | Metaverse and Medical Diagnosis: A Blockchain-Based Digital Twinning Approach Based on MobileNetV2 Algorithm for Cervical Vertebral Maturation |
| title_short | Metaverse and Medical Diagnosis: A Blockchain-Based Digital Twinning Approach Based on MobileNetV2 Algorithm for Cervical Vertebral Maturation |
| title_sort | metaverse and medical diagnosis a blockchain based digital twinning approach based on mobilenetv2 algorithm for cervical vertebral maturation |
| topic | dental surgery dentistry digital twins deep learning CNN advanced mathematical models |
| url | https://www.mdpi.com/2075-4418/13/8/1485 |
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