The design of an fast Fourier filter for enhancing diagnostically relevant structures - endodontic files

BACKGROUND The endodontic working length is commonly determined by electronic apex locators and intraoral periapical radiographs. No algorithms for the automatic detection of endodontic files in dental radiographs have been described in the recent literature. METHOD Teeth from the mandibles of pig cadavers were accessed, and digital radiographs of these specimens were obtained using an optical bench. The specimens were then recorded in identical positions and settings after the insertion of endodontic files of known sizes (ISO sizes 10-15). The frequency bands generated by the endodontic files were determined using fast Fourier transforms (FFTs) to convert the resulting images into frequency spectra. The detected frequencies were used to design a pre-segmentation filter, which was programmed using Delphi XE RAD Studio software (Embarcadero Technologies, San Francisco, USA) and tested on 20 radiographs. For performance evaluation purposes, the gauged lengths (measured with a caliper) of visible endodontic files were measured in the native and filtered images. RESULTS The software was able to segment the endodontic files in both the samples and similar dental radiographs. We observed median length differences of 0.52 mm (SD: 2.76 mm) and 0.46 mm (SD: 2.33 mm) in the native and post-segmentation images, respectively. Pearson's correlation test revealed a significant correlation of 0.915 between the true length and the measured length in the native images; the corresponding correlation for the filtered images was 0.97 (p=0.0001). CONCLUSIONS The algorithm can be used to automatically detect and measure the lengths of endodontic files in digital dental radiographs.

[1]  Aaron Fenster,et al.  A real-time biopsy needle segmentation technique using Hough transform. , 2003, Medical physics.

[2]  Richard O. Duda,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972, CACM.

[3]  Bernd Jähne,et al.  Digital Image Processing: Concepts, Algorithms, and Scientific Applications , 1991 .

[4]  Betül Ilhan Kal,et al.  Effect of various digital processing algorithms on the measurement accuracy of endodontic file length. , 2007, Oral surgery, oral medicine, oral pathology, oral radiology, and endodontics.

[5]  Robert M Love,et al.  A comparison of phosphor-plate digital images with conventional radiographs for the perceived clarity of fine endodontic files and periapical lesions. , 2002, Oral surgery, oral medicine, oral pathology, oral radiology, and endodontics.

[6]  J. Lewsey,et al.  Outcome of primary root canal treatment: systematic review of the literature -- Part 2. Influence of clinical factors. , 2007, International endodontic journal.

[7]  Jim R. Parker,et al.  Algorithms for image processing and computer vision , 1996 .

[8]  McDonald Nj,et al.  Radiographic and electronic diagnostic systems. , 1991 .

[9]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[10]  Aaron Fenster,et al.  Oblique needle segmentation and tracking for 3D TRUS guided prostate brachytherapy. , 2005, Medical physics.

[11]  T. J. Stein,et al.  Radiographic "working length" revisited. , 1992, Oral surgery, oral medicine, and oral pathology.

[12]  N P Chandler,et al.  Electronic apex locators. , 2004, International endodontic journal.

[13]  W D McDavid,et al.  Radiographic determination of canal length direct digital radiography versus conventional radiography. , 1994, Journal of endodontics.

[14]  B Röhrig,et al.  Length of endodontic files measured in digital radiographs with and without noise-suppression filters: an ex-vivo study. , 2011, Dento maxillo facial radiology.

[15]  K Gulabivala,et al.  Outcome of secondary root canal treatment: a systematic review of the literature. , 2007, International endodontic journal.

[16]  Stefano Soatto,et al.  Biopsy needle detection in transrectal ultrasound , 2011, Comput. Medical Imaging Graph..

[17]  N. Grzywacz,et al.  Power spectra and distribution of contrasts of natural images from different habitats , 2003, Vision Research.

[18]  J G Burch,et al.  The relationship of the apical foramen to the anatomic apex of the tooth root. , 1972, Oral surgery, oral medicine, and oral pathology.

[19]  Bidyut Baran Chaudhuri,et al.  A survey of Hough Transform , 2015, Pattern Recognit..

[20]  Aude Oliva,et al.  Global semantic classification of scenes using power spectrum templates , 1999 .

[21]  A Fenster,et al.  An algorithm for automatic needle localization in ultrasound-guided breast biopsies. , 2000, Medical physics.

[22]  Josef Kittler,et al.  A survey of the hough transform , 1988, Comput. Vis. Graph. Image Process..

[23]  L. Lin,et al.  A concordance correlation coefficient to evaluate reproducibility. , 1989, Biometrics.