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DOI 10.1007/bf03168339

Медицинская библиотека · Journal of digital imaging · 2000

Diagnostic accuracy of film-based, TIFF, and wavelet compressed digital temporomandibular joint images.

Trapnell C J, Scarfe W C, Cook J H, Silvejra A M, Regennitter F J, Haskell B S

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Аннотация

The purpose of this research was to determine if digitization and the application of various compression routines to digital images of temporomandibular joint (TMJ) radiographs would diminish observer accuracy in the detection of specific osseous characteristics associated with TMJ degenerative joint disease (DJD). Nine observers viewed 6 cropped hard-copy radiographic films each of 34 TMJs (17 radiographic series). Regions of interest measuring 2 in x 2 in were digitized using an 8-bit scanner with transparency adapter at 300 dpi. The images were placed into a montage of 6 images and stored as tagged image file format (TIFF), compressed at 4 levels (25:1, 50:1, 75:1, and 100:1) using a wavelet algorithm, and displayed to the observers on a computer monitor. Their observations regarding condylar faceting, sclerosis, osteophyte formation, erosion, and abnormal shape were analyzed using ROC. Kappa values were determined for relative condylar size and condylar position within the glenoid fossa. Indices were compared using ANOVA at a significance level of P < .05. Although significant and substantial observer variability was demonstrated, there were no statistically significant differences between image modalities, except for condylar position, in which TIFF and wavelet (at all compression ratios) performed better than the original image. For faceting, wavelet 100:1 performed better than radiographic film images. Little actual image file reduction was achieved at compression ratios above 25:1.

Для цитирования: Trapnell C J, Scarfe W C, Cook J H, Silvejra A M, Regennitter F J, Haskell B S. Diagnostic accuracy of film-based, TIFF, and wavelet compressed digital temporomandibular joint images.. Journal of digital imaging. 2000. DOI: 10.1007/bf03168339.

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