Program including abstracts as pdf available here
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Program including abstracts as pdf available here
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OP 54<br />
Title<br />
THE DESIGN OF FFT FILTERS FOR THE ENHANCEMENT OF DIAGNOSTIC-RELEVANT<br />
STRuCTuRES<br />
Authors<br />
D. bRuELLMANN 1 , S. SANDER 1 , u. zELLER 2 , R. SCHuLzE 1<br />
Affiliations<br />
1 Department of Orla Surgery, University Medical Center, Mainz, GERMANY, 2 orangedental<br />
GmbH & Co. KG, Biberach, GERMANY<br />
Body<br />
Objectives:<br />
The aim of this study is to illustrate the effect of a newly developed filter to enhance endodontic<br />
needles in digital dental radiography.<br />
Methods:<br />
The teeth of the cadaver pork mandibles were accessed. Digital radiographs of these specimens<br />
were obtained using an optical bench. Specimens were then recorded in the exact same position<br />
having had endodontic needles of known size inserted. The resulting images were converted<br />
into their power spectra using a f<strong>as</strong>t Fourier transform to determine the frequencies caused<br />
by the endodontic needles. The encountered frequencies were used to enhance the endodontic<br />
needles. Lengths were me<strong>as</strong>ured in native and filtered images for performance evaluation.<br />
Results:<br />
The encountered frequencies were used for the design of the filter which w<strong>as</strong> programmed<br />
using DelphiXE RAD Studio (Embarcadero Technologies, San Francisco, USA) and tested on 20<br />
radiographs. The software is able to enhance the endodontic needles in the samples and in<br />
similar dental radiographs. Lengths showed a median difference of 0.52 mm (sd 2.76 mm) in<br />
native images and 0.46 mm (sd 2.33 mm) in filtered images, respectively. Pearson’s correlation<br />
test revealed a significant correlation of 0.915 between gauged length and me<strong>as</strong>urement in<br />
native images and 0.97 for filtered images, respectively (p = 0.0001).<br />
Conclusions:<br />
This study shows that we can design filters for every structure, which we can model <strong>as</strong> an<br />
adjunct to digital dental radiographs. The algorithm can be used for automatic detection of<br />
endodontic needles in digital dental radiographs. The technique described <strong>here</strong> could be extended<br />
to simulated carious lesions.<br />
Keywords<br />
F<strong>as</strong>t Fourier Transform, Image Enhancement, Computer Assisted Me<strong>as</strong>urement<br />
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