A novel dual-band bandpass filter (BPF) is developed by using the proposed coplanar waveguide (CPW) stepped impedance square ring loaded resonator (SI-SRLR). To construct two passbands, the resonant ...property of the presented SI-SRLR is firstly investigated. Then, two coupled resonators are used to constitute a dual-band BPF with the center frequencies at 2.4 GHz and 5.8 GHz. Besides, an additional short-circuited conducting stub is introduced between two resonators to prevent excessive coupling to obtain moderate bandwidths. Furthermore, multiple transmission zeros are produced at each side of passbands, which highly improve the selectivity of the passband and the attenuation in stopband. Good simulated results demonstrate the benefits of the proposed resonator and design method.
Chest X-rays (CXRs) are commonly utilized as a low-dose modality for lung screening. Nonetheless, the efficacy of CXRs is somewhat impeded, given that approximately 75% of the lung area overlaps with ...bone, which in turn hampers the detection and diagnosis of diseases. As a remedial measure, bone suppression techniques have been introduced. The current dual-energy subtraction imaging technique in the clinic requires costly equipment and subjects being exposed to high radiation. To circumvent these issues, deep learning-based image generation algorithms have been proposed. However, existing methods fall short in terms of producing high-quality images and capturing texture details, particularly with pulmonary vessels. To address these issues, this paper proposes a new bone suppression framework, termed BS-Diff, that comprises a conditional diffusion model equipped with a U-Net architecture and a simple enhancement module to incorporate an autoencoder. Our proposed network cannot only generate soft tissue images with a high bone suppression rate but also possesses the capability to capture fine image details. Additionally, we compiled the largest dataset since 2010, including data from 120 patients with high-definition, high-resolution paired CXRs and soft tissue images collected by our affiliated hospital. Extensive experiments, comparative analyses, ablation studies, and clinical evaluations indicate that the proposed BS-Diff outperforms several bone-suppression models across multiple metrics. Our code can be accessed at https://github.com/Benny0323/BS-Diff.
As the precondition of image recognition, the effective image segmentation plays the significant role of the following image processing. In this paper, it is proposed to apply Bayesian ...decision-making theory based on minimum error probability to gray image segmentation. On the assumption that the gray values accord with the probability distribution of Gaussian finite mixture model in image feature space, EM algorithm is used to estimate the parameters of mixture model. In order to improve the convergence speed of EM algorithm, a novel and feasible method called weighted equal interval sampling is presented to obtain the contracted sample set. Consequently, the computation task of EM algorithm is greatly reduced and efficiency is improved. An approximate MMIC algorithm of Bayesian Information Criterion is employed to determine quickly how many regions should be segmented on a given gray image. The automatic image segmentation can be executed with the method mentioned above. We demonstrate the effectiveness and feasibility of our method on a set of natural and synthetic images.
PDF
