X ray images are essential data sources for checking the condition of the teeth, gums, jaws, and bone structure of the mouth. Tooth recognition is fundamental in image processing based diagnoses. In most previous recognition studies, only four axis based object detection models have been considered because they perform normal object detection while the object is resting on a flat surface. However, because the teeth have various orientations, the existing four axis based model leads to inaccurate and inefficient recognition results. Thus, in this study, we propose a five axis based object detection model that considers the orientation of the tooth. Based on a tooth image dataset labeled using the five axis ground truth, our proposed method processed five axis annotated data by employing a variant of the faster region based convolutional neural network. In the experiment, our proposed method outperformed the existing four axis approach, both qualitatively and quantitatively. The experimental results indicated that the proposed five axis based recognition model will be an important basis for a dental image based diagnosis.
We describe the spin polarization–induced chirogenic electropolymerization of achiral 2 vinylpyridine, which forms a layer of enantioenhanced isotactic polymer on the electrode. The product formed is enantioenriched in asymmetric carbon polymer. To confirm the chirality of the polymer film formed on the electrode, we also measured its electron spin polarization properties as a function of its thickness. Two methods were used: First, spin polarization was measured by applying magnetic contact atomic force microscopy, and second, magnetoresistance was assessed in a sandwich like four point contact structure. We observed high spin selective electron transmission, even for a layer thickness of 120 nm. A correlation exists between the change in the circular dichroism signal and the change in the spin polarization, as a function of thickness. The spin filtering efficiency increases with temperature.
The purpose of this study was to evaluate corneal irregular astigmatism of patients with granular and lattice corneal dystrophy (GCD and LCD). 70 GCD, 35 LCD, and 81 control eyes were included. Anterior and posterior corneal topographic data obtained from anterior segment optical coherence tomography were expanded into four components via Fourier harmonic analysis. These components were compared with healthy eyes and the association between each component and best-corrected visual acuity (BCVA) was investigated. Anterior and posterior components increased in both GCD and LCD eyes. Anterior and posterior components of GCD2, anterior of LCD type 1 (LCD1), posterior of LCD type IIIA (LCD 3A), and type IV (LCD4) significantly increased. BCVA was significantly associated with anterior and posterior components in LCD eyes but not in GCD. The anterior components of LCD1, anterior and posterior of LCD3A, and posterior of LCD4 , were positively correlated with BCVA. As conclusions, in GCD eyes, anterior and posterior components differed from those of the control but BCVA was not significantly associated with them. In LCD eyes, the anterior and posterior components increased, and BCVA was significantly associated with the anterior and posterior components.