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Objective: Preoperative localization in patients with primary or secondary hyperparathyroidism before radiofrequency ablation (RFA) is crucial. There is currently a lack of consensus regarding imaging protocol. Evaluating the diagnostic performance of ultrasound, four-dimensional computed tomography (4D-CT), and technetium 99m-sestamibi single-photon-emission-computed tomography/computed tomography (SPECT/CT) is necessary for RFA of hyperparathyroidism. Methods: This retrospective study recruited patients with primary or secondary hyperparathyroidism who underwent ultrasound, 4D-CT, and SPECT/CT before RFA at a single institution. The sensitivity, accuracy, and receiver operating characteristic curve analysis were used to evaluate the diagnostic performance of the imaging modalities. Results: A total of 33 patients underwent RFA for hyperparathyroidism (8 patients with primary hyperparathyroidism, 25 patients with secondary hyperparathyroidism). Ultrasound had the highest sensitivity (0.953) and accuracy (0.943), while 4D-CT had higher sensitivity and accuracy than SPECT/CT (sensitivity/accuracy, 4D-CT vs. SPECT/CT: 0.929/0.920 vs. 0.741/0.716). Combined ultrasound with 4D-CT and the three combined modalities achieved equivalent, and the highest, diagnostic performance (sensitivity 1.000, accuracy 0.989). The lesion length and volume were important predictors of the diagnostic performance of 4D-CT and SPECT/CT (area under curve of length in 4D-CT/volume in 4D-CT/length in SPECT/volume in SPECT: 0.895/0.834/0.767/0.761). Conclusion: Combined ultrasound with 4D-CT provides optimal preoperative localization prior to RFA in patients with primary or secondary hyperparathyroidism. The length and volume of parathyroid lesions are determinative of the diagnostic performance of 4D-CT and SPECT/CT.

In medical practice, the scanned image of the patient between the patient and the doctor is confidential. If info is stored on a single server and the server is successfully attacked, it is possible to expose confidential information. Password encryption and data authentication are commonly used to protect patient data, however, encryption and data authentication are computationally expensive and take time to execute on a mobile device. In addition, it is not easy for the patient details related to medical images to leak if the hacked image are not visual.Therefore, in this paper, we propose a way to make medical images remain untouched in this sense. We use our method to quickly create two shadows from two medical images and store them on two servers. Revealing a shadow image does nothing to compromise the confidentiality of a patient’s health. This method is based on Hamming code. With low computational cost, the proposed scheme is suitable for tablet, pamphlets and other mobile devices.

This study analyzes the corrosion inhibition efficiency of sodium molybdate (SM) solution on weldment specimens in 1 M HCl, based on H2 bubbles detection. The detection of the bubbles produced by the corrosion process is achieved by a YOLOv4 deep learning algorithm. The results indicate that the corrosion rate is higher on the weld metal zone than on the base metal zone in the same solution, which might be attributed to the coarser grain of the weld metal zone and the stability of the produced oxide layer. The addition of sodium molybdate was discovered to boost the stability of the oxide layer, hence enhancing the specimens’ corrosion resistance. The overall inhibitory efficiency of the sodium molybdate solution was 59% for the weld metal (WM) (0.4 g/L), 52% for the heat-affected zone (HAZ) (0.2 g/L), and 37% for the base metal (BM) (0.2 g/L). The object detection algorithm models showed 97% for the mAP and 0.98 for recall. The minimum average bubble detected for the WM was 0.353 /mm2 at an SM concentration of 0.4 g/L, while the HAZ was 0.612 /mm2 at 0.2 g/L, and the BM was 1.055 /mm2 at 0.2 g/L. The results of the bubbles detection appeared to be consistent with the corrosion experiment outcomes obtained by the potentiodynamic polarization and hydrogen volume measurement tests. This experiment validates the distinctiveness of the different weld zones in terms of the inhibitor concentration required for successful corrosion prevention, as well as the potential of analyzing corrosion using machine learning algorithms for object detection.

How can the compound eye of insects capture the prey so accurately andquickly? This interesting issue is explored from the perspective of computer vision insteadof from the viewpoint of biology. The focus is on performance evaluation of noiseimmunity for motion recovery using the single-row superposition-type planar compound-like eye (SPCE). The SPCE owns a special symmetrical framework with tremendousamount of ommatidia inspired by compound eye of insects. The noise simulates possibleambiguity of image patterns caused by either environmental uncertainty or low resolutionof CCD devices. Results of extensive simulations indicate that this special visualconfiguration provides excellent motion estimation performance regardless of themagnitude of the noise. Even when the noise interference is serious, the SPCE is able todramatically reduce errors of motion recovery of the ego-translation without any type offilters. In other words, symmetrical, regular, and multiple vision sensing devices of thecompound-like eye have statistical averaging advantage to suppress possible noises. Thisdiscovery lays the basic foundation in terms of engineering approaches for the secret of thecompound eye of insects.