# Automated Dental Fracture Detection using High Resolution CBCT and Advanced Image Analysis

> **NIH NIH R44** · KITWARE, INC. · 2021 · $855,962

## Abstract

PROJECT SUMMARY
Epidemiological studies indicate that cracked teeth are the third most common cause of tooth loss in
industrialized countries. Histological studies demonstrate that all cracks are colonized by bacteria, which have
 the potential to cause intensely painful pulpal and periapical infections. The early detection of cracks (incomplete
fractures) followed by appropriate interventions to prevent crack propagation are effective strategies to prevent
 infections and avert tooth loss. Current tools used to diagnose cracks are inadequate and there is an imperative
need to develop an objective and reliable method to detect cracks. During our Phase I project, we developed
 and tested a novel algorithm for crack detection on extracted human teeth. Using machine learning and imaging
 features extracted from three-dimensional (3D) wavelets, we demonstrated enhanced crack detection hr-CBCT.
We now propose to further refine this technology and to validate it clinically. Our hypothesis is that our method
 increases the predictive validity of hr-CBCT in detecting cracks. This development will happen with close clinical
 guidance. Also, we will collaborate with CBCT hardware vendors to increase the impact of our commercialization
plan. This proposal addresses the need for quantitative, reproducible, and evidence-based ways to detect
cracks in teeth, that can potentially lead to improved tooth loss prevention.

## Key facts

- **NIH application ID:** 10322271
- **Project number:** 2R44DE027574-02A1
- **Recipient organization:** KITWARE, INC.
- **Principal Investigator:** Beatriz Paniagua
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $855,962
- **Award type:** 2
- **Project period:** 2021-09-21 → 2023-09-21

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10322271

## Citation

> US National Institutes of Health, RePORTER application 10322271, Automated Dental Fracture Detection using High Resolution CBCT and Advanced Image Analysis (2R44DE027574-02A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10322271. Licensed CC0.

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