434 research outputs found
Tooth Instance Segmentation from Cone-Beam CT Images through Point-based Detection and Gaussian Disentanglement
Individual tooth segmentation and identification from cone-beam computed
tomography images are preoperative prerequisites for orthodontic treatments.
Instance segmentation methods using convolutional neural networks have
demonstrated ground-breaking results on individual tooth segmentation tasks,
and are used in various medical imaging applications. While point-based
detection networks achieve superior results on dental images, it is still a
challenging task to distinguish adjacent teeth because of their similar
topologies and proximate nature. In this study, we propose a point-based tooth
localization network that effectively disentangles each individual tooth based
on a Gaussian disentanglement objective function. The proposed network first
performs heatmap regression accompanied by box regression for all the
anatomical teeth. A novel Gaussian disentanglement penalty is employed by
minimizing the sum of the pixel-wise multiplication of the heatmaps for all
adjacent teeth pairs. Subsequently, individual tooth segmentation is performed
by converting a pixel-wise labeling task to a distance map regression task to
minimize false positives in adjacent regions of the teeth. Experimental results
demonstrate that the proposed algorithm outperforms state-of-the-art approaches
by increasing the average precision of detection by 9.1%, which results in a
high performance in terms of individual tooth segmentation. The primary
significance of the proposed method is two-fold: 1) the introduction of a
point-based tooth detection framework that does not require additional
classification and 2) the design of a novel loss function that effectively
separates Gaussian distributions based on heatmap responses in the point-based
detection framework.Comment: 11 pages, 7 figure
Does the Experience of Using Metaverse Affect the Relationship between Social Identity, Psychological Ownership, and Engagement?
Cylindrical Tightly Coupled Dipole Array Antenna
A cylindrical tightly coupled dipole array antenna (C-TCDA) based on Munk’s planar TCDA theory, the elements of which are placed on the surface of a cylinder, is introduced and analyzed in this study. The explicit field components of the transverse electromagnetic (TEM) waves existing in the C-TCDA for both polarizations are given. Moreover, the embedding impedance characteristics of the C-TCDA are presented and compared with those of planar TCDA. Analysis results show that the C-TCDA has similar impedance characteristics to the planar TCDA and thus can be implemented in a similar manner. The design of a dual-polarized omnidirectional octagonal TCDA, which has a 3.08:1 bandwidth (from 0.73 GHz to 2.25 GHz) with a voltage standing wave radiation (VSWR) of less than 2 and a low gain variation of less than 1.8 dB at broadside for both polarizations, is also proposed. When scanning up to ±30° in the θ-direction, the array operates in the same frequency band with a VSWR of less than 2.05 and a low gain variation of less than 2 dB for both polarizations
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