Magister Scientiae Dentium - MSc(Dent) / Cephalometric 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).
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uwc/oai:etd.uwc.ac.za:11394/8795 |
| Date | January 2021 |
| Creators | Indermun, Suvarna |
| Contributors | Shaik, Shoayeb |
| Publisher | University of Western Cape |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Rights | University of Western Cape |
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