Dental CLAIRES: Contrastive LAnguage Image REtrieval Search for Dental Research.

AMIA Jt Summits Transl Sci Proc

University of Texas Health Science Center at Houston, School of Biomedical Informatics, Houston, Texas, USA.

Published: June 2023

Learning about diagnostic features and related clinical information from dental radiographs is important for dental research. However, the lack of expert-annotated data and convenient search tools poses challenges. Our primary objective is to design a search tool that uses a user's query for oral-related research. The proposed framework, ontrastive nguage mage trieval earch for dental research, Dental CLAIRES, utilizes periapical radiographs and associated clinical details such as periodontal diagnosis, demographic information to retrieve the best-matched images based on the text query. We applied a contrastive representation learning method to find images described by the user's text by maximizing the similarity score of positive pairs (true pairs) and minimizing the score of negative pairs (random pairs). Our model achieved a hit@3 ratio of 96% and a Mean Reciprocal Rank (MRR) of 0.82. We also designed a graphical user interface that allows researchers to verify the model's performance with interactions.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10283104PMC

Publication Analysis

Top Keywords

dental claires
8
dental
6
claires contrastive
4
contrastive language
4
language image
4
image retrieval
4
retrieval search
4
search dental
4
dental learning
4
learning diagnostic
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!