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

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Background

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.

Aim

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.

Data

Project typeMaster thesis
ECTS30
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

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

Examination

Final presentation and final report/thesis

Contact

Prof. Dr. Oliver Amft

  • Job title: Director
  • Address:
    Henkestr. 91, Geb. 7
    91052 Erlangen
  • Phone number: +49 9131 85-23601
  • Email: oliver.amft@fau.de
Friedrich-Alexander-Universität Erlangen-Nürnberg