Stereo Video Quality Metric Based on Multi-Dimensional Analysis

Stereo video has been widely applied in various video systems in recent years. Therefore, objective stereo video quality metric (SVQM) is highly necessary for improving the watching experience. However, due to the high dimensional data in stereo video, existing metrics have some defects in accuracy and robustness. Based on the characteristics of stereo video, this paper considers the coexistence and interaction of multi-dimensional information in stereo video and proposes an SVQM based on multi-dimensional analysis (MDA-SVQM). Specifically, a temporal-view joint decomposition (TVJD) model is established by analyzing and comparing correlation in different dimensions and adaptively decomposes stereo group of frames (sGoF) into different subbands. Then, according to the generation mechanism and physical meaning of each subband, histogram-based and LOID-based features are extracted for high and low frequency subband, respectively, and sGoF quality is obtained by regression. Finally, the weight of each sGoF is calculated by spatial-temporal energy weighting (STEW) model, and final stereo video quality is obtained by weighted summation of all sGoF qualities. Experiments on two stereo video databases demonstrate that TVJD and STEW adopted in MDA-SVQM are convincible, and the overall performance of MDA-SVQM is better than several existing SVQMs.

Active Dosimetry with the Ability to Distinguish Pulsed and Non-Pulsed Dose Rate Contributions

This paper presents the concept of an active dosimetry system and its operational regime for pulsed radiation dose rate measurements. The plastic scintillator is suggested to be used for absorbed dose rate measurements. As long as the detector can be considered tissue equivalent, the energy weighting of pile-up events in terms of the dose is achieved. The real-time distinction of pulsed and non-pulsed dose rate contributions is based on the time structure of a single interaction and requires only basic information about the beam time structure (pulses duration and period). The detector connected to a fully digital signal processing board creates an active dosimetry system with adjustable parameters. Such a system was used for absorbed dose rate measurements in pulsed photon field mimicking radiation field outside the bunker of a medical LINAC, but also in the presence of a constant radiation component. The results show a linear dependence of a pulsed radiation contribution on the accelerator current in the investigated range of the total dose rate up to 8 μGy/h.

Spatial Unmasking Effect on Speech Reception Threshold in the Median Plane

This study examined whether the spatial unmasking effect operates on speech reception thresholds (SRTs) in the median plane. SRTs were measured using an adaptive staircase procedure, with target speech sentences and speech-shaped noise maskers presented via loudspeakers at −30°, 0°, 30°, 60° and 90°. Results indicated a significant median plane spatial unmasking effect, with the largest SRT gain obtained for the −30° elevation of the masker. Head-related transfer function analysis suggests that the result is associated with the energy weighting of the ear-input signal of the masker at upper-mid frequencies relative to the maskee.

Automated detection of bone splinters in DEXA phantoms using deep neural networks

Dual energy radiographic imaging is a method to provide material information and can be used to differentiate between various tissue types. Dual energy X-ray absorption (DEXA) can be applied for breast density, osteoporosis or bone fracture analysis. To support radiologists with the assessment of DEXA images, machine learning can be applied. Specifically, deep convolutional neural networks (DCNNs) can be used for medical image analysis. In this work a DCNN is proposed and evaluated for automated detection of bone splinters in DEXA phantom images. The image data consists of 47 phantoms with (35) and without (12) bone splinters. Material decomposition and energy weighting results in additional image channels. Various DCNN architectures and parameters were explored. A classification rate in regions with 90 % and without 99 % bone splinters was achieved.