INTRODUCTION: The objective of this study was to show the practical application of computer-aided techniques for detecting root canal orifices through the access cavity using a video camera mounted on a microscope. METHODS: A minimum distance classification image recognition algorithm was tested in an in vitro study to assess the possibilities of computer-aided recognition of root canal orifices. A Motic DM143 digital stereo microscope (Motic Germany GmbH, Wetzlar, Germany) was used because it includes a video camera that can be connected via USB1.1 to any computer. RESULTS: The newly developed software is capable of communicating with a video camera and can automatically detect the root canal orifices in all teeth used in this study. A total of 165 extracted human teeth (molars and premolars) were used as test data to collect 8,250 images via screenshots for the evaluation of the detection quality. The software provided a detection sensitivity of 90.1%, with only 11.9% of the images as false-positive detections. CONCLUSION: The study shows that computer-aided recognition of root canal orifices with video cameras is possible.
INTRODUCTION: The objective of this study was to show the practical application of computer-aided techniques for detecting root canal orifices through the access cavity using a video camera mounted on a microscope. METHODS: A minimum distance classification image recognition algorithm was tested in an in vitro study to assess the possibilities of computer-aided recognition of root canal orifices. A Motic DM143 digital stereo microscope (Motic Germany GmbH, Wetzlar, Germany) was used because it includes a video camera that can be connected via USB1.1 to any computer. RESULTS: The newly developed software is capable of communicating with a video camera and can automatically detect the root canal orifices in all teeth used in this study. A total of 165 extracted human teeth (molars and premolars) were used as test data to collect 8,250 images via screenshots for the evaluation of the detection quality. The software provided a detection sensitivity of 90.1%, with only 11.9% of the images as false-positive detections. CONCLUSION: The study shows that computer-aided recognition of root canal orifices with video cameras is possible.