Evaluation of Denoising Performance of ResNet Deep Learning Model for Ultrasound Images Corresponding to Two Frequency Parameters.

Ultrasound imaging is widely used for accurate diagnosis due to its noninvasive nature and the absence of radiation exposure, which is achieved by controlling the scan frequency. In addition, Gaussian and speckle noises degrade image quality. To address this issue, filtering techniques are typically used in the spatial domain. Recently, deep learning models have been increasingly applied in the field of medical imaging. In this study, we evaluated the effectiveness of a convolutional neural network-based residual network (ResNet) deep learning model for noise reduction when Gaussian and speckle noises were present. We compared the results with those obtained from conventional filtering techniques. A dataset of 500 images was prepared, and Gaussian and speckle noises were added to create noisy input images. The dataset was divided into training, validation, and test sets in an 8:1:1 ratio. The ResNet deep learning model, comprising 16 residual blocks, was trained using optimized hyperparameters, including the learning rate, optimization function, and loss function. For quantitative analysis, we calculated the normalized noise power spectrum, peak signal-to-noise ratio, and root mean square error. Our findings showed that the ResNet deep learning model exhibited superior noise reduction performance to median, Wiener, and median-modified Wiener filter algorithms.

Optimal dual-energy computed tomography scan parameters to detect small-sized urinary stones and their composition.

To investigate the optimal scanning parameters of dual-energy computed tomography (DECT), which can accurately determine sensitivity (the detectability of urinary stones) and accuracy (the composition matching of urinary stones), and to apply them to clinical trials. Fifteen urinary stones were chemically analyzed, and their chemical compositions were considered a reference standard with which we compared the uric acid (UA) and non-UA compositions determined using DECT. The urinary stones were placed inside a bolus and scanned with a dual-source CT scanner under various selected dual-energy conditions (A to X) using various solid water phantom thicknesses. These datasets were analyzed using the Siemens syngo.via software tool (integrated into the CT system) for matching the sensitivity and accuracy assessments. This study showed that 80% of the highest sensitivity (detection of urinary stones) and 92% of the highest accuracy (composition matching of urinary stones) were achieved under condition A (a collimation beam width setting of 2 × 32 × 0.6 mm, an automatic exposure control setting of 80/sn140 peak kilovoltage, and a slice thickness of 0.5/0.5 mm) (P < 0.05). Application of the DECT energy parameters presented in the study will help identify the sensitivity and accuracy of UA and non-UA stone analysis, even in patients with small-sized urinary stones and in conditions difficult for analysis.

Improvement of image quality using amplitude-based respiratory gating in PET-computed tomography scanning.

OBJECTIVES: This study sought to provide data supporting the expanded clinical use of respiratory gating by assessing the diagnostic accuracy of breathing motion correction using amplitude-based respiratory gating. METHODS: A respiratory movement tracking device was attached to a PET-computed tomography scanner, and images were obtained in respiratory gating mode using a motion phantom that was capable of sensing vertical motion. Specifically, after setting amplitude changes and intervals according to the movement cycle using a total of nine combinations of three waveforms and three amplitude ranges, respiratory motion-corrected images were reconstructed using the filtered back projection method. After defining areas of interest in the acquired images in the same image planes, statistical analyses were performed to compare differences in standardized uptake value (SUV), lesion volume, full width at half maximum (FWHM), signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). RESULTS: SUVmax increased by 89.9%, and lesion volume decreased by 27.9%. Full width at half maximum decreased by 53.9%, signal-to-noise ratio increased by 11% and contrast-to-noise ratio increased by 16.3%. Optimal results were obtained when using a rest waveform and 35% duty cycle, in which the change in amplitude in the respiratory phase signal was low, and a constant level of long breaths was maintained. CONCLUSIONS: These results demonstrate that respiratory-gated PET-CT imaging can be used to accurately correct for SUV changes and image distortion caused by respiratory motion, thereby providing excellent imaging information and quality.

Encoding scheme using quantum dots for single logical qubit information onto four-photon decoherence-free states.

We designed an encoding scheme, using quantum dots (QDs), for single logical qubit information by encoding quantum information onto four-photon decoherence-free states to acquire immunity against collective decoherence. The designed scheme comprised of QDs, confined in single-sided cavities (QD-cavity systems), used for arbitrary quantum information, encoded onto four-photon decoherence-free states (logical qubits). For our scheme, which can generate the four-photon decoherence-free states, and can encode quantum information onto logical qubits, high efficiency and reliable performance of the interaction between the photons and QD-cavity systems is essential. Thus, through our analysis of the performance of QD-cavity systems under vacuum noise and sideband leakage, we demonstrate that the encoding scheme for single logical qubit information could be feasibly implemented.

Photonic scheme of discrete quantum Fourier transform for quantum algorithms via quantum dots.

We propose an optical scheme of discrete quantum Fourier transform (DQFT) via ancillary systems using quantum dots (QDs) confined in single-sided cavities (QD-cavity systems). In our DQFT scheme, the main component is a controlled-rotation k (CRk) gate, which utilizes the interactions between photons and QDs, consisting of two QD-cavity systems. Since the proposed CRk gate can be experimentally implemented with high efficiency and reliable performance, the scalability of multi-qubit DQFT scheme can also be realized through the simple composition of the proposed CRk gates via the QD-cavity systems. Subsequently, in order to demonstrate the performance of the CRk gate, we analyze the interaction between a photon and a QD-cavity system, and then indicate the condition to be efficient CRk gate with feasibility under vacuum noise and sideband leakage.

Estimation of leakage rate of air from a fume hood in a radioisotope laboratory using CFD simulations.

The leakage rate of air from a fume hood is an important factor for calculating the internal exposure at a workplace using the dose conversion factors recommended by the International Atomic Energy Agency. In this study, the leakage rate from a fume hood was estimated in a radioisotope laboratory using computational fluid dynamics simulations. For this purpose, a three-dimensional fume hood model was built using CAD software. In this model, the leakage rate was calculated to be 3%, with face velocities between 0.1 and 1.0 m/s at the sash opening of the fume hood. This rate rapidly decreased to zero as the face velocities decreased to less than 0.1 m/s.

Implementation of controlled quantum teleportation with an arbitrator for secure quantum channels via quantum dots inside optical cavities.

We propose a controlled quantum teleportation scheme to teleport an unknown state based on the interactions between flying photons and quantum dots (QDs) confined within single- and double-sided cavities. In our scheme, users (Alice and Bob) can teleport the unknown state through a secure entanglement channel under the control and distribution of an arbitrator (Trent). For construction of the entanglement channel, Trent utilizes the interactions between two photons and the QD-cavity system, which consists of a charged QD (negatively charged exciton) inside a single-sided cavity. Subsequently, Alice can teleport the unknown state of the electron spin in a QD inside a double-sided cavity to Bob's electron spin in a QD inside a single-sided cavity assisted by the channel information from Trent. Furthermore, our scheme using QD-cavity systems is feasible with high fidelity, and can be experimentally realized with current technologies.

Distribution of hybrid entanglement and hyperentanglement with time-bin for secure quantum channel under noise via weak cross-Kerr nonlinearity.

We design schemes to generate and distribute hybrid entanglement and hyperentanglement correlated with degrees of freedom (polarization and time-bin) via weak cross-Kerr nonlinearities (XKNLs) and linear optical devices (including time-bin encoders). In our scheme, the multi-photon gates (which consist of XKNLs, quantum bus [qubus] beams, and photon-number-resolving [PNR] measurement) with time-bin encoders can generate hyperentanglement or hybrid entanglement. And we can also purify the entangled state (polarization) of two photons using only linear optical devices and time-bin encoders under a noisy (bit-flip) channel. Subsequently, through local operations (using a multi-photon gate via XKNLs) and classical communications, it is possible to generate a four-qubit hybrid entangled state (polarization and time-bin). Finally, we discuss how the multi-photon gate using XKNLs, qubus beams, and PNR measurement can be reliably performed under the decoherence effect.