OPG-SHAP: A Dental AI Tool for Explaining Learned Orthopantomogram Image Recognition

dc.contributor.authorHirunchavarod N.
dc.contributor.authorDangsungnoen L.
dc.contributor.authorThongprasant K.
dc.contributor.authorPhuphatham P.
dc.contributor.authorPrathansap N.
dc.contributor.authorSributsayakarn N.
dc.contributor.authorPornprasertsuk-Damrongsri S.
dc.contributor.authorJirarattanasopha V.
dc.contributor.authorIntharah T.
dc.contributor.correspondenceHirunchavarod N.
dc.contributor.otherMahidol University
dc.date.accessioned2024-09-17T18:28:09Z
dc.date.available2024-09-17T18:28:09Z
dc.date.issued2024-01-01
dc.description.abstractWe propose OPG-SHAP, a tool for extracting insight of the trained deep learning model for an Orthopantomograms (OPGs). The tool allows user to understand the areas that influence the model's predictions through SHAP (SHapley Additive exPlanations) interpretability. The tool automatically identify the regions within the OPG image that influence the model's decision-making through YOLO-based object detection model that trained to detect over 20 classes of dental region in OPGs with an AverageIoU = 0.795, mAP = 0.989, Precision = 0.986, Recall = 0.987, and F1 score = 0.986. When a user inputs an OPG image and model into the OPG-SHAP tool, the output highlights the positions the model considers important for its decision, indicated by positive and negative SHAP values.
dc.identifier.citation2024 International Technical Conference on Circuits/Systems, Computers, and Communications, ITC-CSCC 2024 (2024)
dc.identifier.doi10.1109/ITC-CSCC62988.2024.10628217
dc.identifier.scopus2-s2.0-85203604359
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/101229
dc.rights.holderSCOPUS
dc.subjectComputer Science
dc.subjectEngineering
dc.titleOPG-SHAP: A Dental AI Tool for Explaining Learned Orthopantomogram Image Recognition
dc.typeConference Paper
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85203604359&origin=inward
oaire.citation.title2024 International Technical Conference on Circuits/Systems, Computers, and Communications, ITC-CSCC 2024
oairecerif.author.affiliationFaculty of Science, Khon Kaen University
oairecerif.author.affiliationMahidol University, Faculty of Dentistry
oairecerif.author.affiliationKhon Kaen University

Files

Collections