Image Processing on IOPA Radiographs: A comprehensive case study on Apical Periodontitis
This work addresses a domain-specific problem in oral diagnostics, providing incremental improvements to the diagnostic procedure.
The paper tackles the problem of diagnosing apical periodontitis from IOPA radiographs by applying image processing and feature extraction techniques, resulting in improved speed and accuracy with a focus on reducing true negative and false positive cases.
With the recent advancements in Image Processing Techniques and development of new robust computer vision algorithms, new areas of research within Medical Diagnosis and Biomedical Engineering are picking up pace. This paper provides a comprehensive in-depth case study of Image Processing, Feature Extraction and Analysis of Apical Periodontitis diagnostic cases in IOPA (Intra Oral Peri-Apical) Radiographs, a common case in oral diagnostic pipeline. This paper provides a detailed analytical approach towards improving the diagnostic procedure with improved and faster results with higher accuracy targeting to eliminate True Negative and False Positive cases.