Phoacouastic (PA) imaging has been gaining attention as a new imaging modality that can non-invasively visualize blood vessels inside biological tissues. In this paper, the reconstruction process of PA, and its technical issues. In the process of imaging large body parts through multi-scan fusion, alignment turns out to be an important issue, since body motion degrades image quality. In this paper, we carefully examine the characteristics of PA images and propose a novel registration method that achieves better alignment while effectively decomposing the shot volumes into low-rank foreground (blood vessels), dense background (noise), and sparse complement (corruption) components on the basis of the PA characteristics. The results of experiments using a challenging real dataset demonstrate the efficacy of the proposed method, which significantly improved image quality, and had the best alignment accuracy among the state-of-the-art methods tested. We also introduce several clinical application of photoacoustic imaging, such as planning of flap surgery.

In recent years, the term “digital transformation” has been used and is being applied in various fields. In the field of medical radiation protection, visualization of invisible radiation using virtual reality technology is thought to lead to a better understanding of radiation protection. We are developing educational materials that simulate and visualize the spread of radiation in various radiological examinations. Although a head-mounted display can be used to create a highly immersive environment for virtual reality, it is not suitable for teaching a large number of students at a time. The use of 3-D and 4-D scattering volume data for radiation protection education is a good way to provide radiation protection education to radiological technologists who do not have expert knowledge of radiation, and to provide them with the opportunity to learn about invisible radiation. It is expected to be effective in improving intuitive understanding of the spread and appropriate methods of care.

The early detections of osteoporosis and osteopenia are required to avoid the painful and life-altering bone fractures, but the screening rate is still limited all over the world. Therefore, to detect and alert people to their lower bone mineral densities (BMDs), the accessible and easy methods are needed. In this study, we developed the fast-screening method for osteoporosis by using chest X-ray images taken frequently and then evaluated the performance of proposed method. We used both BMD values measured by dual-energy X-ray absorptiometry (DXA) and chest X-ray images from 711 females. In the proposed method, by using deep convolutional neural network (DCNN), images were classified into normal BMD cases and lower BMD cases. DCNN was trained by ROI images which are cropped first lumber spine from chest X-ray images. The sensitivity, specificity, overall accuracies and AUC were respectively 87.95%, 79.60%, 84.18% and 0.9134. We developed and validated the osteoporosis screening algorithm based on DCNN by using chest X-ray images. The proposed system has high potential as a classification tool, and there is a possibility that the vertebral bodies on chest X-ray images show characteristic of lower BMD.

The median filter processing is applied to some flat panel detector systems used for defect pixel compensation. The aim of our study was to examine the effect of median filter processing for the presampled MTF measurement to determine whether the presampled MTF measurement could be performed using the edge method. First, we simulated the edge image, and evaluated the effect of the inclination angle of the edge, the kernel size, noise. Then, we applied median filter processing to a reference edge image and examined the effect of the presampled MTF.

The effect of median filtering did not generate moire patterns in the simulated edge images and reference median filtering image. Although the MTF could be measured, the effect of the median filter was different because of the noise level. For the presampled MTF measurement of a reference edge image with a median filter, the relative error with respect to the true value decreased in the MTF by approximately 3.4% at the maximum. Although the effect of median filtering was shown, the presampled MTF measurements using the edge method can be calculated in the same clinical settings. However, the median filter should be eliminated wherever measurement accuracy is required.

Dental cone beam computed tomography (CBCT) is now widely available withboth 180° and 360°imaging. Radiation dose and motion artifacts are lower for 180° than 360° imaging. Therefore, 180° imaging may be useful in children who are more sensitive toradiation exposure and have difficulty in controlling their body movements. Thepurpose of this study was to clarify the effect of rotation angle on imagequality from modulation transfer function (MTF) and noise power spectrum (NPS) and to determine the optimal imaging tube voltage byobtaining the tube voltage characteristics of FPD. As a result, resolution wasnot affected by rotation angle. NPS was higher in 180°imaging than in 360° imaging. System performance (SP) function was lower in 180° imaging than in 360° imaging, withoutchanging the frequency characteristics. The higher the tube voltage, the higherthe value of SP function and the lower the radiation dose. The optimal tubevoltage for dental CBCT will be 90 kV.