Reduction of Angularly-Varying-Data Truncation in C-Arm CBCT Imaging.

C-arm cone-beam computed tomography (CBCT) has been used increasingly as an imaging tool for yielding 3D anatomical information about the subjects in surgical and interventional procedures. In the clinical applications, the limited field-of-view (FOV) of C-arm CBCT can lead to significant data truncation, resulting in image artifacts that can obscure low contrast tumor embedded within soft-tissue background, thus limiting the utility of C-arm CBCT. The truncation issue can become serious as most of the surgical and interventional procedures would involve devices and tubes that are placed outside the FOV of C-arm CBCT and thus can engender angularly-varying-data truncation.

3D segmentation of maxilla in cone-beam computed tomography imaging using base invariant wavelet active shape model on customized two-manifold topology.

Recent advances in cone-beam computed tomography (CBCT) have rapidly enabled widepsread applications of dentomaxillofacial imaging and orthodontic practices in the past decades due to its low radiation dose, high spatial resolution, and accessibility. However, low contrast resolution in CBCT image has become its major limitation in building skull models. Intensive hand-segmentation is usually required to reconstruct the skull models.

In vitro evaluation of new approach to digital dental model articulation.

Purpose: The purpose of the present study was to evaluate the accuracy of our newly developed approach to digital dental model articulation.

Materials And Methods: Twelve sets of stone dental models from patients with craniomaxillofacial deformities were used for validation. All the models had stable occlusion and no evidence of early contact.

Automated digital dental articulation.

Articulating digital dental models is often inaccurate and very time-consuming. This paper presents an automated approach to efficiently articulate digital dental models to maximum intercuspation (MI). There are two steps in our method.

An automatic and robust algorithm of reestablishment of digital dental occlusion.

In the field of craniomaxillofacial (CMF) surgery, surgical planning can be performed on composite 3-D models that are generated by merging a computerized tomography scan with digital dental models. Digital dental models can be generated by scanning the surfaces of plaster dental models or dental impressions with a high-resolution laser scanner. During the planning process, one of the essential steps is to reestablish the dental occlusion.

An interactive geometric technique for upper and lower teeth segmentation.

Due to the complexity of the dental models in semantics of both shape and form, a fully automated method for the separation of the lower and upper teeth is unsuitable while manual segmentation requires painstakingly user interventions. In this paper, we present a novel interactive method to segment the upper and lower teeth. The process is performed on 3D triangular mesh of the skull and consists of four main steps: reconstruction of 3D model from teeth CT images, curvature estimation, interactive segmentation path planning using the shortest path finding algorithm, and performing actual geometric cut on 3D models using a graph cut algorithm.