Oct 19, 2024 · In this study, we propose a semantic segmentation framework based on convolutional neural networks (CNNs) aimed at segmenting teeth in 2D panoramic radiographs.

Oct 21, 2024 · Semantic segmentation of panoramic images plays a crucial role in many applications, such as scene understanding, autonomous navigation, and ...

The proposed network comprised backbone network, local segmentation and a weight network. The backbone network extracts the features from image. The local ...

Convolutional Neural Network-Based Multi-scale Semantic Segmentation for Two-Dimensional Panoramic X-Rays of Teeth. https://doi.org/10.1007/978-3-031-72396 ...

The primary functions of CNN in recognizing dental objects on panoramic radiographs include 3 tasks: classification, detection, and segmentation. A schematic ...

Sep 10, 2024 · Our method extracts multi-scale tooth features from the designed residual omni-dimensional dynamic convolution and the designed two-stream ...

The purpose of this study was to evaluate periodontal bone loss and periodontitis stage on dental periapical radiographs using deep convolutional neural ...

An automatic teeth segmentation CNN model can accurately and efficiently identify the boundaries and contours of individual teeth in dental radiographs or 3D ...

In this study, we propose a new algorithm, for instance, segmentation of the different teeth in panoramic dental X-rays. Methods: An instance segmentation model ...

Feb 5, 2024 · This paper discusses the deep learning methods of tooth segmentation on dental panoramic radiographs (DPRs), cone-beam computed tomography (CBCT) ...