Cephalometric landmark detection: Artificial intelligence vs human examination

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dc.contributor.advisorShaik, Shoayeb
dc.contributor.authorIndermun, Suvarna
dc.date.accessioned2022-03-03T08:39:14Z
dc.date.accessioned2024-04-15T11:03:01Z
dc.date.available2022-03-03T08:39:14Z
dc.date.available2024-04-15T11:03:01Z
dc.date.issued2021
dc.descriptionMagister Scientiae Dentium - MSc(Dent)en_US
dc.description.abstractCephalometric landmark detection is important for accurate diagnosis and treatment planning. The most common cause of random errors, in both computer-aided cephalometry and manual cephalometric analysis, is inconsistency in landmark detection. These methods are time-consuming. As a result, attempts have been made to automate cephalometric analysis, to improve the accuracy and precision of landmark detection whilst also minimizing errors caused by clinician subjectivity.This mini-thesis aimed to determine the precision of two cephalometric landmark identification methods, namely an artificial intelligence programme (BoneFinder®) and a computer-assisted examination software (Dolphin ImagingTM).en_US
dc.identifier.urihttps://hdl.handle.net/10566/10805
dc.language.isoenen_US
dc.publisherUniversity of Western Capeen_US
dc.rights.holderUniversity of Western Capeen_US
dc.subjectArtificial intelligenceen_US
dc.subjectHuman examinationen_US
dc.subjectMachine learningen_US
dc.subjectRadiologyen_US
dc.subjectOrthodonticsen_US
dc.titleCephalometric landmark detection: Artificial intelligence vs human examinationen_US

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