A simple AI-enabled method for quantifying bacterial adhesion on dental materials

Hao Dinga Dental Materials Science, Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Pokfulam, Hong KongView further author information

Yunzhen Yanga Dental Materials Science, Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Pokfulam, Hong KongView further author information

Xin Lib Restorative Dental Sciences, Faculty of Dentistry, The University of Hong Kong, Pokfulam, Hong Kong;c Department of Stomatology Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen, ChinaView further author information

Gary Shun-Pan Cheungb Restorative Dental Sciences, Faculty of Dentistry, The University of Hong Kong, Pokfulam, Hong KongView further author information

Jukka Pekka Matinlinnaa Dental Materials Science, Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Pokfulam, Hong KongView further author information

Michael Burrowb Restorative Dental Sciences, Faculty of Dentistry, The University of Hong Kong, Pokfulam, Hong KongView further author information

James Kit-Hon Tsoia Dental Materials Science, Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Pokfulam, Hong KongCorrespondence[email protected]
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A simple AI-enabled method for quantifying bacterial adhesion on dental materials

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