RESUMO
Due to accurate 3D information, computed tomography (CT), especially cone-beam CT or dental CT, has been widely used for diagnosis and treatment planning in dentistry. Axial images acquired from both medical and dental CT scanners can generate synthetic panoramic images similar to typical 2D panoramic radiographs. However, the conventional way to reconstruct the simulated panoramic images is to manually draw the dental arch on axial images. In this paper, we propose a new fast algorithm for automatic detection of the dental arch. Once the dental arch is computed, a series of synthetic panoramic images as well as a ray-sum panoramic image can be automatically generated. We have tested the proposed algorithm on 120 CT axial images and all of them can provide the decent estimate of the dental arch. The results show that our proposed algorithm can mostly detect the correct dental arch.
Assuntos
Tomografia Computadorizada de Feixe Cônico/métodos , Arco Dental/anatomia & histologia , Radiografia Panorâmica/métodos , Algoritmos , HumanosRESUMO
OBJECTIVE: The use of the Semmes-Weinstein (SW) monofilament test is recommended as a screening method for diabetic neuropathy. It offers an important chance to prevent further complications of diabetic foot. We aimed to develop a prototype Robotic Monofilament Inspector that can be used as a standard machine for screening of diabetic neuropathy. METHODS: Development was divided into three parts: computer software, control box, and Robotic Monofilament Inspector. The examiner conducted the SW test (by hand and by robotic inspector), vibration perception threshold, and Toronto Clinical Scoring System without knowledge of patient information. The unpaired t test or Wilcoxon rank-sum test was used to determine the differences between independent groups in terms of continuous outcomes, while the χ(2) test was used to determine categorical outcomes. Agreement between the various diabetic neuropathy tests was measured using the kappa statistic. RESULTS: The SW test and vibration perception threshold were more valid tests for neuropathy than the Toronto test. The robotic test was in excellent agreement with the two former tests and appeared to be valid (kappa statistic, 0.35-0.81). Another indirect evidence for the validity of the robotic test was the finding that diabetic patients with foot ulcers had a higher prevalence of neuropathy (77%vs. 38%). This might indicate that the robotic test was more valid than the manual test. CONCLUSION: The Robotic Monofilament Inspector could be used as a simple screening machine. This prototype may be developed further for routine clinical use.