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Hepatobiliary surgery based on intelligent image segmentation technology
Liver disease is an important disease that seriously threatens human health. It accounts for the highest proportion in various malignant tumors, and its incidence rate and mortality are on the rise, seriously affecting human health. Modern imaging has developed rapidly, but the application of image...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
De Gruyter
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476479/ https://www.ncbi.nlm.nih.gov/pubmed/37671090 http://dx.doi.org/10.1515/biol-2022-0674 |
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author | Wang, Fuchuan Xiao, Chaohui Jia, Tianye Pan, Liru Du, Fengxia Wang, Zhaohai |
author_facet | Wang, Fuchuan Xiao, Chaohui Jia, Tianye Pan, Liru Du, Fengxia Wang, Zhaohai |
author_sort | Wang, Fuchuan |
collection | PubMed |
description | Liver disease is an important disease that seriously threatens human health. It accounts for the highest proportion in various malignant tumors, and its incidence rate and mortality are on the rise, seriously affecting human health. Modern imaging has developed rapidly, but the application of image segmentation in liver tumor surgery is still rare. The application of image processing technology represented by artificial intelligence (AI) in surgery can greatly improve the efficiency of surgery, reduce surgical complications, and reduce the cost of surgery. Hepatocellular carcinoma is the most common malignant tumor in the world, and its mortality is second only to lung cancer. The resection rate of liver cancer surgery is high, and it is a multidisciplinary surgery, so it is necessary to explore the possibility of effective switching between different disciplines. Resection of hepatobiliary and pancreatic tumors is one of the most challenging and lethal surgical procedures. The operation requires a high level of doctors’ experience and understanding of anatomical structures. The surgical segmentation is slow and there may be obvious complications. Therefore, the surgical system needs to make full use of the relevant functions of AI technology and computer vision analysis software, and combine the processing strategy based on image processing algorithm and computer vision analysis model. Intelligent optimization algorithm, also known as modern heuristic algorithm, is an algorithm with global optimization performance, strong universality, and suitable for parallel processing. This algorithm generally has a strict theoretical basis, rather than relying solely on expert experience. In theory, the optimal solution or approximate optimal solution can be found in a certain time. This work studies the hepatobiliary surgery through intelligent image segmentation technology, and analyzes them through intelligent optimization algorithm. The research results showed that when other conditions were the same, there were three patients who had adverse reactions in hepatobiliary surgery through intelligent image segmentation technology, accounting for 10%. The number of patients with adverse reactions in hepatobiliary surgery by conventional methods was nine, accounting for 30%, which was significantly higher than the former, indicating a positive relationship between intelligent image segmentation technology and hepatobiliary surgery. |
format | Online Article Text |
id | pubmed-10476479 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | De Gruyter |
record_format | MEDLINE/PubMed |
spelling | pubmed-104764792023-09-05 Hepatobiliary surgery based on intelligent image segmentation technology Wang, Fuchuan Xiao, Chaohui Jia, Tianye Pan, Liru Du, Fengxia Wang, Zhaohai Open Life Sci Research Article Liver disease is an important disease that seriously threatens human health. It accounts for the highest proportion in various malignant tumors, and its incidence rate and mortality are on the rise, seriously affecting human health. Modern imaging has developed rapidly, but the application of image segmentation in liver tumor surgery is still rare. The application of image processing technology represented by artificial intelligence (AI) in surgery can greatly improve the efficiency of surgery, reduce surgical complications, and reduce the cost of surgery. Hepatocellular carcinoma is the most common malignant tumor in the world, and its mortality is second only to lung cancer. The resection rate of liver cancer surgery is high, and it is a multidisciplinary surgery, so it is necessary to explore the possibility of effective switching between different disciplines. Resection of hepatobiliary and pancreatic tumors is one of the most challenging and lethal surgical procedures. The operation requires a high level of doctors’ experience and understanding of anatomical structures. The surgical segmentation is slow and there may be obvious complications. Therefore, the surgical system needs to make full use of the relevant functions of AI technology and computer vision analysis software, and combine the processing strategy based on image processing algorithm and computer vision analysis model. Intelligent optimization algorithm, also known as modern heuristic algorithm, is an algorithm with global optimization performance, strong universality, and suitable for parallel processing. This algorithm generally has a strict theoretical basis, rather than relying solely on expert experience. In theory, the optimal solution or approximate optimal solution can be found in a certain time. This work studies the hepatobiliary surgery through intelligent image segmentation technology, and analyzes them through intelligent optimization algorithm. The research results showed that when other conditions were the same, there were three patients who had adverse reactions in hepatobiliary surgery through intelligent image segmentation technology, accounting for 10%. The number of patients with adverse reactions in hepatobiliary surgery by conventional methods was nine, accounting for 30%, which was significantly higher than the former, indicating a positive relationship between intelligent image segmentation technology and hepatobiliary surgery. De Gruyter 2023-08-30 /pmc/articles/PMC10476479/ /pubmed/37671090 http://dx.doi.org/10.1515/biol-2022-0674 Text en © 2023 the author(s), published by De Gruyter https://creativecommons.org/licenses/by/4.0/This work is licensed under the Creative Commons Attribution 4.0 International License. |
spellingShingle | Research Article Wang, Fuchuan Xiao, Chaohui Jia, Tianye Pan, Liru Du, Fengxia Wang, Zhaohai Hepatobiliary surgery based on intelligent image segmentation technology |
title | Hepatobiliary surgery based on intelligent image segmentation technology |
title_full | Hepatobiliary surgery based on intelligent image segmentation technology |
title_fullStr | Hepatobiliary surgery based on intelligent image segmentation technology |
title_full_unstemmed | Hepatobiliary surgery based on intelligent image segmentation technology |
title_short | Hepatobiliary surgery based on intelligent image segmentation technology |
title_sort | hepatobiliary surgery based on intelligent image segmentation technology |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476479/ https://www.ncbi.nlm.nih.gov/pubmed/37671090 http://dx.doi.org/10.1515/biol-2022-0674 |
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