Showing 4 results for Ultrasound
Sayed Mahmoud Sakhaei, A.mahlooji Far, Hassan Ghassemian,
Volume 2, Issue 2 (4-2006)
Abstract
Contrast resolution and detail resolution are two important parameters in
ultrasound imaging. This paper presents a new method to enhance these parameters,
simultaneously. A parallel auxiliary beamformer has been employed whose weightings are
such that an estimation of the leaked signal through the main beamformer is obtained. Then
the output of main beamformer is modified according to the estimated leaked signal. The
efficiency of our adaptive method is demonstrated by applying it over an experimental data
set and provided an enhancement of about 22 percent in lateral resolution and 15-20 dB in
contrast resolution. This method also has the advantages of simplicity and possibility of real
time implementation.
O. Mahmoudi Mehr, M. R. Mohammadi, M. Soryani,
Volume 19, Issue 3 (9-2023)
Abstract
Speckle noise is an inherent artifact appearing in medical images that significantly lowers the quality and accuracy of diagnosis and treatment. Therefore, speckle reduction is considered as an essential step before processing and analyzing the ultrasound images. In this paper, we propose an ultrasound speckle reduction method based on speckle noise model estimation using a deep learning architecture called “speckle noise-based inception convolutional denoising neural network" (SNICDNN). Regarding the complicated nature of speckle noise, an inception module is added to the first layer to boost the power of feature extraction. Reconstruction of the despeckled image is performed by introducing a mathematical method based on solving a quadratic equation and applying an image-based inception convolutional denoising autoencoder (IICDAE). The results of various quantitative and qualitative evaluations on real ultrasound images demonstrate that SNICDNN outperforms the state-of-the-art methods for ultrasound despeckling. SNICDNN achieves 0.4579 dB and 0.0100 additional gains on average for PSNR and SSIM, respectively, compared to other methods. Denoising ultrasound based on its noise model estimation is not only a novel approach in comparison to traditional denoising autoencoder models but also due to the fact that it uses mathematical solutions to recover denoised images, SNICDNN shows a greater power in ultrasound despeckling.
V. Esmaeili, M. Mohassel Feghhi,
Volume 19, Issue 3 (9-2023)
Abstract
The coronavirus disease or COVID-19, as a global disease, is an unprecedented health care crisis due to increasing mortality and its high rate of infection. Patients usually show significant complications in the respiratory system. This disease is caused by SARS-CoV-2. Decreasing the time of diagnosis is essential for reducing deaths and low spreading of the virus. Also, using the optimal tool in the pediatric setting and Intensive care unit (ICU) is required. Therefore, using lung ultrasound is recommended. It does not have any radiation and it has a lower cost. However, it makes noisy and low-quality data. In this paper, we propose a novel approach called Uniform Local Binary Pattern on Five intersecting Planes and convolutional neural Network (ULBPFP-Net) that overcomes the said limitation. We extract worthwhile features from five planes for feeding a network. Our experiments confirm the success of the ULBPFP-Net in COVID-19 diagnosis compared to the previous approaches.
Seyyedeh Ensiyeh Hashemi, Hamid Behnam,
Volume 21, Issue 3 (8-2025)
Abstract
Increasing the frame rate of ultrasound imaging while keeping image quality is important for following fast movements, especially the heart. There are different modalities for B-mode image recording, including line-by-line scanning with linear, phased, convex array, synthetic aperture imaging (STA), plane waves (PWI), then the combination of plane waves (CPWI), and so on. Researchers have tried to increase the frame rate in each case using different methods. Three approaches for this aim are data acquisition, post-processing, and beamforming. This article reviews these approaches and their solutions for compensating image quality reduction. Ultrafast ultrasound imaging, which provides exceptional temporal resolution (high frame rate), is promising in diagnosing heart diseases due to its ability to capture rapid heart movements. It can record images faster than conventional imaging, usually exceeding 1000 frames per second. This can be achieved through plane wave imaging (PWI). However, high frame rate data acquisition can lead to a decrease in image quality. Transmitting at different angles and then combining plane wave imaging is a popular method to enhance PWI quality but reduces the frame rate by the number of angles. As a result, researchers have aimed to increase the temporal resolution while compensating for the loss of quality.
