During the past years several innovative and technological developments have been made in oral surgery. Today, digitized dental casts are common for simulation and planning of orthodontic interventions. In order to work with these models, knowing the exact position of the teeth is of high importance. In this paper, we present a new method for tooth segmentation with minimal user interaction. At...

Tooth Cementum Annulation (TCA) is an age estimation method carried out on thin cross sections of the root of the human tooth. Age is computed by adding the tooth eruption age to the count of annual incremental lines which are called tooth rings and appear in the cementum band. Algorithms to denoise and segment the digital image of the tooth section are considered a crucial step towards compute...

Tooth Cementum Annulation (TCA) is an age estimation method carried out on thin cross sections of the root of the human tooth. Age is computed by adding the tooth eruption age to the count of annual incremental lines which are called tooth rings and appear in the cementum band. Algorithms to denoise and segment the digital image of the tooth section are considered a crucial step towards compute...

Background: Accurate brain tissue segmentation from magnetic resonance (MR) images is an important step in analysis of cerebral images. There are software packages which are used for brain segmentation. These packages usually contain a set of skull stripping, intensity non-uniformity (bias) correction and segmentation routines. Thus, assessment of the quality of the segmented gray matter (GM), ...

We first describe how to “fuzzify” the estimated binary columns to create a [0,1]-valued column. Werefer to this [0,1] -valued column as the soft segmentation column of the noisy spectrogram column.Similarly to the collection of soft segmentation columns as the soft segmentation image, or simply asthe soft segmentation. The band-dependent posterior probability that the hard segmentation columnv...

This review presents an in-depth study of the literature on segmentation methods applied in dental imaging. Ten segmentation methods were studied and categorized according to the type of the segmentation method (region-based, threshold-based, cluster-based, boundary-based or watershed-based), type of Xray images used (intra-oral or extra-oral) and characteristics of the dataset used to evaluate...

IntroductionTooth segmentation on cone-beam computed tomographic (CBCT) imaging is a labor-intensive task considering the limited contrast resolution and potential disturbance by various artifacts. Fully automated tooth cannot be achieved merely relying CBCT intensity variations. This study aimed to develop validate an artificial intelligence (AI)-driven tool for imaging.MethodsA total of 433 D...