Literature DB >> 20089061

The effects of digital image enhancement on the detection of vertical root fracture.

Kivanç Kamburoğlu1, Sema Murat, Selcen Yüksel Pehlivan.   

Abstract

AIM: To determine the effects of digital image enhancement on observer ability to detect experimentally induced vertical root fractures (VRF).
MATERIAL AND METHODS: A total of 64 extracted human mandibular premolar teeth were used in this study. In 32 teeth, VRFs were created in the bucco-lingual planes by gently tapping with screw-type root-canal pins. The remaining 32 intact teeth served as a control group. Digital images were obtained using a charge coupled device sensor. Three observers separately examined the original and four types of digitally enhanced images (enhanced using sharpness, zoom-in, reverse-contrast, and pseudo-3D functions) at 1-week intervals. All teeth were evaluated using a 5-point scale for the presence/absence of VRF. Evaluations of each image set were repeated 1 month after the initial viewings. Kappa coefficients were calculated to investigate the degree of intra- and inter-observer agreement. The areas under the receiver operating characteristic (ROC) curves (Az values) were calculated using the MedCalc statistical software. ROC values for each image type, observer and viewing were compared using t-tests. A level of alpha = 0.05 was considered significant.
RESULTS: Kappa coefficients for intra-observer agreement ranged from 0.304 to 0.679. Inter-observer agreement kappa values ranged from 0.109 to 0.399 for the first reading and from 0.106 to 0.380 for the second reading. Statistical comparisons between Az values for each observer showed no significant differences (P > 0.05) among image types.
CONCLUSION: There were no differences in diagnostic outcomes among differently enhanced images in the in vitro detection of VRF.

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Year:  2010        PMID: 20089061     DOI: 10.1111/j.1600-9657.2009.00841.x

Source DB:  PubMed          Journal:  Dent Traumatol        ISSN: 1600-4469            Impact factor:   3.333


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