Sensitivity of modern multislice CT for subarachnoid haemorrhage at incremental timepoints after headache onset: a 10-year analysis

BackgroundCT performed within 6 hours of headache onset is highly sensitive for the detection of subarachnoid haemorrhage (SAH). Beyond this time frame, if the CT is negative for blood, a lumbar puncture is often performed. Technology improvements in image noise reduction, resolution and motion artefact have enhanced the performance of multislice CT (MSCT) and may have further improved sensitivity. We aimed to describe how the sensitivity to SAH of modern MSCT changes with time from headache onset.MethodsThis was a retrospective analysis of electronic data collected as part of routine care among all patients presenting to Christchurch Hospital diagnosed with a SAH between 1 January 2008 and 31 December 2017. Patients were imaged with MSCT. The primary outcome was the proportion of patients with spontaneous aneurysmal SAH (identified via coding and confirmed by clinical and radiological records) that had a positive MSCT. The secondary outcome was the proportion of patients with any type of spontaneous SAH that had a positive MSCT.ResultsThere were 347 patients with an SAH of whom 260 were aneurysmal SAH. MSCT identified 253 (97.3%) of all aneurysmal SAH and 332 (95.7%) of all SAH. The sensitivity of MSCT was 99.6% (95% CI 97.6 to 100) for aneurysmal SAH and 99.0% (95% CI 97.1 to 99.8) for all SAH at 48 hours after headache onset. At 24 hours after headache onset, the sensitivity for aneurysmal SAH was 100% (95% CI 98.3 to 100).ConclusionThese data suggest that it may be possible to extend the timeframe from headache onset within which modern MSCT can be used to rule out aneurysmal SAH.

Image enhancement in wavelet domain based on histogram equalization and median filter

During the acquisition of a new digital image, noise may be introduced as a result of the production process. Image enhancement is used to alleviate problems caused by noise. In this work, the purpose is to propose, apply, and evaluate enhancement approaches to images by selecting suitable filters to produce improved quality and performance results. The new method proposed for image noise reduction as an enhancement process employs threshold and histogram equalization implemented in the wavelet domain. Different types of wavelet filters were tested to obtain the best results for the image noise reduction process. Also, the effect of canceling one or more of the high-frequency bands in the wavelet domain was tested. The mean square error and peak signal to noise ratio are used for measuring the improvement in image noise reduction. A comparison made with two related works shows the superiority of the methods proposed and implemented in this research. The proposed methods of applying the median filter before and after the histogram equalization methods produce improvement in performance and efficiency compared to the case of using discrete wavelet transform only, even with the cases of multiresolution discrete wavelet transform and the cancellation step.

Proposal of Edge-Preserving, Image Noise Reduction Filter for Using L2-Norm

Images taken by digital cameras include noise. The image recognition rate decreases with increasing noise. Reducing noise is essential for improving the accuracy of image recognition. Low-pass filters, such as a Gaussian filter (GF), are often used to reduce noise from images. Low-pass filters can reduce noise. However, low-pass filters always blur the edges. As the edge blur becomes stronger, the accuracy of edge and feature detection of image recognition worsens. Therefore, we propose a noise reduction filter for images that can preserve edges by combining the GF and the L2-norm. The proposed method is expected to improve the image quality and, consequently, the accuracy of image recognition.

Application of Image Recognition Method Based on Diffusion Equation in Film and Television Production

On the basis of studying the basic theory of anisotropic diffusion equation, this paper focuses on the application of anisotropic diffusion equation in image recognition film production. In order to further improve the application performance of P-M (Perona-Malik) anisotropic diffusion model, an improved P-M anisotropic diffusion model is proposed in this paper, and its application in image ultrasonic image noise reduction is discussed. The experimental results show that the model can effectively suppress the speckle noise and preserve the edge features of the image. Based on the image recognition technology, an image frame testing system is designed and implemented. The method of image recognition diffusion equation is used to extract and recognize the multilayer feature points of the test object according to the design of artificial neural network. To a certain extent, it improves the accuracy of image recognition and the audience rating of film and television. Use visual features of the film and television play in similarity calculation for simple movement scene segmentation problem, at the same time, the camera to obtain information, use the lens frame vision measuring the change of motion of the camera, and use weighted diffusion equation and the visual similarity of lens similarity calculation and motion information, by considering the camera motion of image recognition, effectively solve the sports scene of oversegmentation problem such as fighting and chasing.

A Quantized Convolutional Neural Network Implemented With Memristor for Image Denoising and Recognition

The interference of noise will cause the degradation of image quality, which can have a negative impact on the subsequent image processing and visual effect. Although the existing image denoising algorithms are relatively perfect, their computational efficiency is restricted by the performance of the computer, and the computational process consumes a lot of energy. In this paper, we propose a method for image denoising and recognition based on multi-conductance states of memristor devices. By regulating the evolution of Pt/ZnO/Pt memristor wires, 26 continuous conductance states were obtained. The image feature preservation and noise reduction are realized via the mapping between the conductance state and the image pixel. Furthermore, weight quantization of convolutional neural network is realized based on multi-conductance states. The simulation results show the feasibility of CNN for image denoising and recognition based on multi-conductance states. This method has a certain guiding significance for the construction of high-performance image noise reduction hardware system.

Enhancement of Cone-Beam Computed Tomography Dental-Maxillofacial Images by Sampling Kantorovich Algorithm

In this paper, we establish a procedure for the enhancement of cone-beam computed tomography (CBCT) dental-maxillofacial images; this can be useful in order to face the problem of rapid prototyping, i.e., to generate a 3D printable file of a dental prosthesis. In the proposed procedure, a crucial role is played by the so-called sampling Kantorovich (SK) algorithm for the reconstruction and image noise reduction. For the latter algorithm, it has already been shown to be effective in the reconstruction and enhancement of real-world images affected by noise in connection to engineering and biomedical problems. The SK algorithm is given by an optimized implementation of the well-known sampling Kantorovich operators and their approximation properties. A comparison between CBTC images processed by the SK algorithm and other well-known methods of digital image processing known in the literature is also given. We finally remark that the above-treated topic has a strong multidisciplinary nature and involves concrete biomedical applications of mathematics. In this type of research, theoretical and experimental disciplines merge in order to find solutions to real-world problems.

Evaluation of left ventricular diastolic function of patients with coronary heart disease by ultrasound images on bilateral filtering image noise reduction algorithm combined with electrocardiogram

Objective: To explore the evaluation of left ventricular diastolic function (LVDF) in patients with coronary heart disease (CHD) using ultrasound images (UI) combined with electrocardiogram (ECG) on bilateral filtering image noise reduction algorithm (BFINRA). Methods: A BFINRA was constructed, and 60 subjects who were investigated were divided into a control group (CG) from June 2019 to November 2019 in Taizhou People’s Hospital, a myocardial infarction group (MIG), and an angina pectoris group (APG). The patient’s LVDF was examined by two-dimensional electrophoresis (2DE) and real-time three-dimensional echocardiography (RT-3DE) combined with ECG. The results showed BFINRA could improve UI quality. Results: Clinical data indicated there were no substantial differences in age, gender, and fasting blood glucose of all subjects. 2DE examination results showed the left ventricular end-diastolic volume (LVEDV), left ventricular end-systolic volume (LVESV), and early diastolic mitral blood flow velocity / early diastolic mitral annulus velocity (E/E’) of MIG were much higher than CG (P<0.05), while the left ventricular ejection fraction (LVEF), E / late diastolic mitral blood flow velocity (E/A) and E’ peak value were sharply decreased (P<0.05);LVESV and E/E’ of APG were increased dramatically (P<0.05), while E peak, E/A and E’ peak were decreased greatly. RT-3DE examination results indicated LVEDV and LVESV of MIG were considerably higher than CG (P<0.05), while LVEF and macrophage resistance factor (MRF) were enormously decreased (P<0.05);LVEDV and LVESV of APG were greatly increased (P<0.05). However, LVEF and MRF were not changed significantly (P>0.05). LVEDV had a remarkable difference (P<0.05), but LVESV and LVEF had no obvious differences (P>0.05). The electrocardiogram results illustrated the increase in QT dispersion (QTd) of MIG and APG was statistically significant (P<0.05) compared with CG, while the negative increase of P-wave terminal force in lead V1 (PTFV1) also had a statistical significance (P<0.05). Correlation analysis revealed that MRF and PTFV1 had positive correlation, while MRF and QTd showed a negative correlation. Conclusion: The combination of UI and ECG could better assess LVDF in CHD patients. doi: https://doi.org/10.12669/pjms.37.6-WIT.4886 How to cite this:Li W. Evaluation of left ventricular diastolic function of patients with coronary heart disease by ultrasound images on bilateral filtering image noise reduction algorithm combined with electrocardiogram. Pak J Med Sci. 2021;37(6):1699-1704. doi: https://doi.org/10.12669/pjms.37.6-WIT.4886 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.