Comput. Biol. Med. - A level-set based approach for anterior teeth segmentation in cone beam computed tomography images.

Tópicos

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Resumo

Cone beam CT (CBCT) has gained popularity in dentistry for 3D imaging of the jaw bones and teeth due to its high resolution and relatively lower radiation exposure compared to multi-slice CT (MSCT). However, image segmentation of the tooth from CBCT is more complex than from MSCT due to lower bone signal-to-noise. This paper describes a level-set method to extract tooth shape from CBCT images of the head. We improve the variational level set framework with three novel energy terms: (1) dual intensity distribution models to represent the two regions inside and outside the tooth; (2) a robust shape prior to impose a shape constraint on the contour evolution; and (3) using the thickness of the tooth dentine wall as a constraint to avoid leakage and shrinkage problems in the segmentation process. The proposed method was compared with several existing methods and was shown to give improved segmentation accuracy.

Resumo Limpo

cone beam ct cbct gain popular dentistri d imag jaw bone teeth due high resolut relat lower radiat exposur compar multislic ct msct howev imag segment tooth cbct complex msct due lower bone signaltonois paper describ levelset method extract tooth shape cbct imag head improv variat level set framework three novel energi term dual intens distribut model repres two region insid outsid tooth robust shape prior impos shape constraint contour evolut use thick tooth dentin wall constraint avoid leakag shrinkag problem segment process propos method compar sever exist method shown give improv segment accuraci

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