Int J Comput Assist Radiol Surg - A two-stage rule-constrained seedless region growing approach for mandibular body segmentation in MRI.

Tópicos

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Resumo

RPOSE: Extraction of the mandible from 3D volumetric images is frequently required for surgical planning and evaluation. Image segmentation from MRI is more complex than CT due to lower bony signal-to-noise. An automated method to extract the human mandible body shape from magnetic resonance (MR) images of the head was developed and tested.METHODS: Anonymous MR images data sets of the head from 12 subjects were subjected to a two-stage rule-constrained region growing approach to derive the shape of the body of the human mandible. An initial thresholding technique was applied followed by a 3D seedless region growing algorithm to detect a large portion of the trabecular bone (TB) regions of the mandible. This stage is followed with a rule-constrained 2D segmentation of each MR axial slice to merge the remaining portions of the TB regions with lower intensity levels. The two-stage approach was replicated to detect the cortical bone (CB) regions of the mandibular body. The TB and CB regions detected from the preceding steps were merged and subjected to a series of morphological processes for completion of the mandibular body region definition. Comparisons of the accuracy of segmentation between the two-stage approach, conventional region growing method, 3D level set method, and manual segmentation were made with Jaccard index, Dice index, and mean surface distance (MSD).RESULTS: The mean accuracy of the proposed method is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The mean accuracy of CRG is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The mean accuracy of the 3D level set method is [Formula: see text] for Jaccard index, [Formula: see text] for Dice index, and [Formula: see text] mm for MSD. The proposed method shows improvement in accuracy over CRG and 3D level set.CONCLUSION: Accurate segmentation of the body of the human mandible from MR images is achieved with the proposed two-stage rule-constrained seedless region growing approach. The accuracy achieved with the two-stage approach is higher than CRG and 3D level set.

Resumo Limpo

rpose extract mandibl d volumetr imag frequent requir surgic plan evalu imag segment mri complex ct due lower boni signaltonois autom method extract human mandibl bodi shape magnet reson mr imag head develop testedmethod anonym mr imag data set head subject subject twostag ruleconstrain region grow approach deriv shape bodi human mandibl initi threshold techniqu appli follow d seedless region grow algorithm detect larg portion trabecular bone tb region mandibl stage follow ruleconstrain d segment mr axial slice merg remain portion tb region lower intens level twostag approach replic detect cortic bone cb region mandibular bodi tb cb region detect preced step merg subject seri morpholog process complet mandibular bodi region definit comparison accuraci segment twostag approach convent region grow method d level set method manual segment made jaccard index dice index mean surfac distanc msdresult mean accuraci propos method formula see text jaccard index formula see text dice index formula see text mm msd mean accuraci crg formula see text jaccard index formula see text dice index formula see text mm msd mean accuraci d level set method formula see text jaccard index formula see text dice index formula see text mm msd propos method show improv accuraci crg d level setconclus accur segment bodi human mandibl mr imag achiev propos twostag ruleconstrain seedless region grow approach accuraci achiev twostag approach higher crg d level set

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