Alveolar nerve unfolding technique for synoptic analysis: visualization and quantification of inferior alveolar nerve tracings in three-dimensional cone-beam computed tomography.

The aim of the technique presented here is to visualize the anatomical context of the inferior alveolar nerve (IAN) canal. For 2 cases, cone-beam computed tomography images of the mandible were obtained from patient files together with the manual preoperative IAN canal tracings. For both cases, similar to simulated panoramic images, a two-dimensional image is extracted from a three-dimensional cone-beam computed tomography image.

On the augmented reproducibility in measurements on 3D orthodontic digital dental models and the definition of feature points.

Objective: The objective of this study was to explore digital measurement methodology on 3-dimensional (3D) dental models. Standardised manipulation and practices have lead to reliable measurements on plaster casts. Identifying landmarks on digital models or digitised plaster casts is fundamentally different from actual measurements.

Vascular active contour for vessel tree segmentation.

In this paper, a novel active contour model is proposed for vessel tree segmentation. First, we introduce a region competition-based active contour model exploiting the gaussian mixture model, which mainly segments thick vessels. Second, we define a vascular vector field to evolve the active contour along its center line into the thin and weak vessels.

Region competition based active contour for medical object extraction.

In this paper, a probabilistic and level set model for three-dimensional medical object extraction is proposed, which is called region competition based active contour. The algorithms are derived by minimizing a region based probabilistic energy function and implemented in a level set framework. An additional speed-controlling term makes the active contour quickly convergent to the actual contour on strong edges, whereas a probabilistic model makes the active contour performing well for weak edges.