Thesis: Near-IR imaging and ML to estimate tooth & gum status

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Dental problems are one of the most prevalent clinical conditions. While oral care method have improved substantially over the last 100 years, incidence rates of tooth and gum problems are persisting or even increasing. For example, bacteria acids erode the tough tooth enamel and subsequently the softer tooth layers. Near-infrared (NIR) light is generally reflected off healthy tooth enamel. Depending on the NIR wavelength, incident light is getting absorbed by a target structure with elevated water content, i.e. compromised structure. In recent years imaging investigations shifted from special-purpose InGaAs cameras to consumer market CMOS technology. However, CMOS camera sensors provide low quantum efficiency at NIR wavelength, thus making image interpretation harder.


Analyse and develop an NIR image interpretation method based on NIR performance-enhanced CMOS cameras. Evaluate and optimise image processing and detection algorithms with actual human tooth samples.


Project typeMaster thesis
LanguageEnglish/ German
PeriodWinter term 2021/22
Presence timeVirtual, mostly working from remote; however some laboratory activity
Useful knowledgeDeep learning, programming, image analysis
Work distribution70% programming and algorithm development, 30% experimentation
StudOn linkN/A
Registratione-mail to Prof. Oliver Amft


Literature recommendations are provided during the meetings. The candidate is further encouraged to research relevant publications on this topic.


Final presentation and final report/thesis


Prof. Dr. Oliver Amft

  • Job title: Director
  • Phone number: +49 9131 85-23601
Friedrich-Alexander-Universität Erlangen-Nürnberg