Multi-frame Technique Research Articles

A Framework for Reconstructing Super-Resolution Magnetic Resonance Images from Sparse Raw Data Using Multilevel Generative Methods

Super-resolution magnetic resonance (MR) scans give anatomical data for quantitative analysis and treatment. The use of convolutional neural networks (CNNs) in image processing and deep learning research have led to super-resolution reconstruction methods based on deep learning. The study offers a G-guided generative multilevel network for training 3D neural networks with poorly sampled MR input data. The author suggest using super-resolution reconstruction (SRR) and modified sparse sampling to address these issues. Image-based Wasserstein GANs retain k-space data sparsity. Wasserstein Generative Adversarial Networks (WGANs) store and represent picture space knowledge. The method obtains null-valued k-space data and repairs fill gaps in the dataset to preserve data integrity. The proposed reconstruction method processes raw data samples and is able to perform subspace synchronization, deblurring, denoising, motion estimation, and super-resolution image production. The suggested algorithm uses different preprocessing methods to deblur and denoise datasets. Preliminary trials contextualize and speed up assessments. Results indicate that reconstructed pictures have better high-frequency features than sophisticated multi-frame techniques. This is supported by rising PSNR, MAE, and IEM measurements. A k-space correction block improves GAN network refinement learning in the suggested method. This block improves the network’s ability to avoid unnecessary data, speeding reconstruction. A k-space correction module can limit the generator’s output to critical lines, allowing the reconstruction of only missing lines. This improves convergence and speeds rebuilding. This study shows that this strategy reduces aliasing artifacts better than contemporaneous and noniterative methods.

RECONSTRUCTION OF HIGH-RESOLUTION HEPATIC TUMOR CT IMAGES USING AN AUGMENTATION-BASED SUPER-RESOLUTION TECHNIQUE

Improving the resolution of medical images is crucial in diagnosis, feature extraction, and data retrieval. A significant group of super-resolution algorithms is multi-frame techniques. However, they are not appropriate to medical data since they need several frames of the same scene, which bring a high risk of radiation or require a considerable acquisition time. We propose a new data augmentation technique and employ it in a multi-frame image reconstruction algorithm to improve the resolution of pathologic liver CT images. The input to our algorithm is a 3D CT-scan of the abdominal region. Neighboring slices are considered to increase the resolution of a single slice. Augmented slices are prepared using the nearby slices and the interpolation approach. The new data is aligned to the original slice, and it is used as an augmented version of the data. Then, a multi-frame scheme is utilized to reconstruct the high-resolution image. Our method’s novelty is to remove the need for multiple scans of a patent to employ multi-resolution techniques in medical applications. The results reveal that the proposed method is superior to conventional interpolation methods and available augmentation techniques. Compared to the tricubic interpolation, the proposed method improved the PSNR by 3.1. Concerning conventional augmentation techniques, it enhanced the SSIM measure by 0.06. The proposed algorithm improved the SSIM by 0.11 compared to traditional interpolation techniques and 0.1 for recent researches. Therefore, a multi-frame super-resolution technique has the potential to reconstruct medical data better.

Motion estimation-based image enhancement in ultrasound imaging

High resolution medical ultrasound (US) imaging is an ongoing challenge in many diagnosis applications and can be achieved either by instrumentation or by post-processing. Though many works have considered the issue of resolution enhancement in optical imaging, very few works have investigated this issue in US imaging. In optics, several algorithms have been proposed to achieve super-resolution (SR) image reconstruction, which consists of merging several low resolution images to create a higher resolution image. However, the straightforward implementation of such techniques for US imaging is unsuccessful, due to the interaction of ultrasound with tissue and speckle. We show how to overcome the limit of SR in this framework by refining the registration part of common multiframe techniques. For this purpose, we investigate motion estimation methods adapted to US imaging. Performance of the proposed technique is evaluated on both realistic simulated US images (providing an estimated best-case performance) and real US sequences of phantom and in-vivo thyroid images. Compared to classical SR methods, our technique brings both quantitative and qualitative improvements. Resolution gain was found to be 1.41 for the phantom sequence and 1.12 for the thyroid sequence and a quantitative study using the phantom further confirmed the spatial resolution enhancement. Furthermore, the contrast-to-noise ratio was increased by 27% and 13% for simulated and experimental US images, respectively.

Hybrid Algorithm for Elastography to Visualize Both Solid and Fluid-Filled Lesions

We propose a novel strain estimation technique that can produce reliable strain images of both solid and fluid-filled lesions. In our method, a kernel-based correlation coefficient technique and a speckle tracking-based strain estimation technique are combined into a single algorithm. The elegance of our algorithm is that fluid-filled lesions are first automatically identified by three selection criteria, and strain in those parts is estimated using the kernel-based correlation coefficient technique. Strain where fluid-filled lesions have not been detected is estimated using a speckle tracking-based algorithm, and then these two estimates are merged to form the final image. Any speckle tracking algorithm can be used in our proposed technique; however, we used a modified version of the direct average spectral strain estimation technique to describe our algorithm. We modified the direct average spectral strain estimation algorithm to track smaller strain variation and to facilitate strain calculation from multiple frames. We describe the performance of our proposed hybrid algorithm using in vivo patient data. Both the solid and fluid-filled lesions are clearly visible in the strain images produced by our proposed approach and are of better quality in terms of contrast-to-noise ratio and border sharpness than the strain images generated by other reported techniques. We also validate the performance of our proposed multiframe technique using experimental phantom data and in vivo patient data. The results reveal that the quality of the strain image can be improved using the multiframe technique compared with its dual-frame counterpart.

Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames

Forward looking infrared (FLIR) detector arrays generally produce spatially undersampled images because the FLIR arrays cannot be made dense enough to yield a sufficiently high spatial sampling frequency. Multi-frame techniques, such as microscanning, are an effective means of reducing aliasing and increasing resolution in images produced by staring imaging systems. These techniques involve interlacing a set of image frames that have been shifted with respect to each other during acquisition. The FLIR system is mounted on a moving platform, such as an aircraft, and the vibrations associated with the platform are used to generate the shifts. Since a fixed number of image frames is required, and the shifts are random, the acquired frames will not fall on a uniformly spaced grid. Furthermore, some of the acquired frames may have almost similar shifts thus making them unusable for high-resolution image reconstruction. In this paper, we utilize a gradient-based registration algorithm to estimate the shifts between the acquired frames and then use a weighted nearest-neighbor approach for placing the frames onto a uniform grid to form a final high-resolution image. Blurring by the detector and optics of the imaging system limits the increase in image resolution when microscanning is attempted at sub-pixel movements of less than half the detector width. We resolve this difficulty by the application of the Wiener filter, designed using the modulation transfer function (MTF) of the imaging system, to the high-resolution image. Simulation and experimental results are presented to verify the effectiveness of the proposed technique. The techniques proposed herein are significantly faster than alternate techniques, and are found to be especially suitable for real-time applications.

Twelve-frame camera for soft X-ray

THE procedure of inertial confinement fusion (ICF) takes place in sub-nanosecond period. In order to investigate the hydrodynamic instability and asymmetry during the implosion, we need to measure the two-dimensional distribution of plasmas temperature and density as well as its relationship with time. For this purpose, an X-ray picosecond multiframe technique has been developed. Traditionally, there are two techniques for gating images, i. e. swept framing and gated microchannel-plate (MCP) framing. Because the former has spatial loss in short exposure time and little dynamic range, the latter is recently in routine

Eight-frame holographic interferometry system for transient plasma diagnostics

A multiframe technique that uses Fresnel holography is described. Splitting of the initial pulse by means of 50/50 beam splitters provides two sets of eight consecutive pulses with approximately the same energy but with different angles. Each interferogram is recorded separately. The technique has been used to obtain time-resolved Fresnel holographic interferograms of transient electrical discharges, such as Z pinch. A frequency-doubled, Q-switched Nd:YAG laser (6-ns FWHM) is used. A delay between consecutive pulses of 10 ns is achieved, and it is mainly limited by the physical size of the laboratory. Interferograms obtained on a gas-embedded Z pinch are shown.