CBCT image based radiomic analysis for condylar resorption after orthognathic surgery.

Objectives: To select and discover features which are highly correlated with condylar resorption (CR) after orthognathic surgery (OS) by a new method.

Materials And Methods: The cone beam computed tomography (CBCT) images were collected from orthognathic patients taken at T1(baseline time point) and T2(within 3-36 months postoperatively). The subjects were divided into the CR group and the control group by using a 2-level scale after registering T1 and T2 images.

Temporomandibular joint CBCT image segmentation via multi-view ensemble learning network.

Accurate segmentation of the temporomandibular joint (TMJ) from cone beam CT (CBCT) images holds significant clinical value for diagnosing temporomandibular joint osteoarthrosis (TMJOA) and related conditions. Convolutional neural network-based medical image segmentation methods have achieved state-of-the-art performance in various segmentation tasks. However, 3D medical images segmentation requires substantial global context and rich spatial semantic information, demanding much more GPU memory and computational resources.

Optimal Training Positive Sample Size Determination for Deep Learning with a Validation on CBCT Image Caries Recognition.

: During deep learning model training, it is essential to consider the balance among the effects of sample size, actual resources, and time constraints. Single-arm objective performance criteria (OPC) was proposed to determine the optimal positive sample size for training deep learning models in caries recognition. : An expected sensitivity (P) of 0.

Deep learning in the diagnosis for cystic lesions of the jaws: a review of recent progress.

Cystic lesions of the gnathic bones present challenges in differential diagnosis. In recent years, artificial intelligence (AI) represented by deep learning (DL) has rapidly developed and emerged in the field of dental and maxillofacial radiology (DMFR). Dental radiography provides a rich resource for the study of diagnostic analysis methods for cystic lesions of the jaws and has attracted many researchers.

Reducing non-realistic deformations in registration using precise and reliable landmark correspondences.

Non-rigid image registration is prone to non-realistic deformations. In this paper, we proposed a novel landmark-correspondence detection algorithm, with which, the non-realistic deformations in image registration can be reduced. Our method consists of the following steps.

CBCT image based segmentation method for tooth pulp cavity region extraction.

Objectives:: A method was proposed to segment the tooth pulp cavity region in cone beam CT) images, which aimed to make the extraction process more efficient and generate more reliable results for further research.

Methods:: Cone beam CT images of 50 teeth from 10 patients were randomly collected with the help of Peking University Hospital of Stomatology. All slice images have a ground truth tooth pulp cavity region delineated by two doctors manually.

An atlas-based multimodal registration method for 2D images with discrepancy structures.

An atlas-based multimodal registration method for 2-dimension images with discrepancy structures was proposed in this paper. Atlas was utilized for complementing the discrepancy structure information in multimodal medical images. The scheme includes three steps: floating image to atlas registration, atlas to reference image registration, and field-based deformation.

Three-dimensional CBCT images registration method for TMJ based on reconstructed condyle and skull base.

Objectives: A method was introduced for three-dimensional (3D) cone-beamCT (CBCT) images registration of temporomandibular joint (TMJ). This study aimed to provide quantitative and qualitative analysis of TMJ bone changes in two-dimensional (2D) and 3D and to provide the technique for computer-aided diagnosis of temporomandibular joint disorders in the future.

Methods: 10 TMJ samples of six patients were obtained from Peking University Hospital of Stomatology.

[A study of trabecular bone structure in the mandibular condyle of healthy young people by cone beam computed tomography].

Objective: To evaluate the feasibility of cone beam computed tomography (CBCT) for the evaluation of trabecular bone structure in mandibular condyle and to investigate the distribution of the trabecular bone structure within mandibular condyle.

Methods: Eighty condyles from 40 healthy young volunteers (aged 20-32) were scanned by CBCT. A coronoid image was acquired of each condyle and divided into 8 regions where regions of interest were specified.