CBCT segmentation of the mandibular canal with both semi-automated and fully automated methods: A systematic review
Clinical Epidemiology and Global Health, ISSN: 2213-3984, Vol: 29, Page: 101760
2024
- 5Captures
- 1Mentions
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures5
- Readers5
- Mentions1
- News Mentions1
- 1
Most Recent News
Research from Manipal Academy of Higher Education in Epidemiology and Global Health Provides New Insights (CBCT segmentation of the mandibular canal with both semi-automated and fully automated methods: A systematic review)
2024 AUG 29 (NewsRx) -- By a News Reporter-Staff News Editor at Health & Medicine Daily -- Fresh data on epidemiology and global health are
Review Description
The application of AI algorithms for the detection of the mandibular canal in Cone Beam Computed Tomography (CBCT) holds immense promise in dentistry. This review aimed to identify the semi and fully automated algorithm to localize the mandibular canal. An extensive search was conducted and, out of which 12 articles are considered for review. The result revealed using various AI algorithms achieved better accuracy in localizing the mandibular canal with reporting sensitivity and specificity above 90 %. In conclusion, it is noted that the application of AI algorithms in dentistry can provide significant benefits like improving the accuracy of reporting.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2213398424002574; http://dx.doi.org/10.1016/j.cegh.2024.101760; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85201499393&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S2213398424002574; https://impressions.manipal.edu/open-access-archive/10105; https://impressions.manipal.edu/cgi/viewcontent.cgi?article=10991&context=open-access-archive
Elsevier BV
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