Phantom-based assessment of focused ultrasound thermal effects with conventional magnetic resonance imaging.

Background And Objective: This study presents key findings from Magnetic Resonance Imaging (MRI)-guided Focused Ultrasound (FUS) sonication experiments in a specialized gel phantom, aimed at demonstrating the effectiveness of using conventional T1-Weighted (T1-W) and T2-Weighted (T2-W) Turbo Spin Echo (TSE) sequences to assess FUS thermal effects and related system performance.

Methods: Three custom-manufactured, single-element spherically focused ultrasonic transducers were utilized in this study. The temporal regression of lesions induced by high-power FUS in the phantom model was investigated within a 3T MRI scanner for both employed sequences.

Magnetic Resonance Imaging monitoring of histotripsy effects in agar phantom.

Background: While the technical aspects of histotripsy have seen significant advancements, research on Magnetic Resonance Imaging (MRI) monitoring remains limited.

Purpose: This preliminary study explored the use of conventional T2-Weighted (T2-W) Turbo Spin Echo (TSE) imaging to monitor histotripsy lesions in a pure agar gel, as a potential research tool for MRI-guided histotripsy (MRgHt).

Methods: Histotripsy experiments were conducted in a 3T MRI scanner using a 2% weight per volume agar solution in water.

DDPM-EMF: a denoising diffusion probabilistic model-based feature-enhancement fusion network for medical image fusion.

Medical image fusion is crucial in clinical applications, combining data from various medical imaging modalities into a single high-quality image to enhance diagnosis. However, existing fusion algorithms suffer from several limitations, including inadequate feature extraction, leading to detail loss, poor inheritance of complementary information between modalities, and insufficient evaluation of color information in color and grayscale fusion tasks. To address these challenges, we propose a novel, to our knowledge, medical image fusion framework based on the denoising diffusion probabilistic model.

Focused Ultrasound Sonications of Tumor Model in Head Phantom under MRI Monitoring: Effect of Skull Obstruction on Focal Heating.

Purpose: This study presents the outcomes of a series of magnetic resonance imaging (MRI)-guided focused ultrasound (MRgFUS) sonications performed on an anatomically accurate head phantom with an embedded tumor simulator to evaluate the effectiveness of partial and complete tumor ablation with obstruction from thin polymer skull mimics.

Materials And Methods: The tumor simulator was subjected to single and grid sonications using a single-element concave transducer integrated with an MRI-compatible focused ultrasound (FUS) robotic system. All experiments were carried out in a high-field MRI scanner utilizing proton resonance frequency thermometry and T2-weighted (T2-W) turbo spin echo (TSE) imaging to evaluate the induced thermal effects.

Optimization of the FPM iterative process based on bright-field spectral overlap rate analysis.

Fourier ptychographic microscopy (FPM) reconstructs high-resolution images through multiple iterations on a large number of sub-images at different angles, a process that is time-consuming. For a long time, various methods for optimizing the efficiency of FPM based on the acquisition process and algorithms have been proposed. However, there has been no specific analysis of the impact that the sub-images involved in the reconstruction have on the final result.

LED-based temporal variant noise model for Fourier ptychographic microscopy.

Fourier ptychographic microscopy (FPM) is a technique to reconstruct a high-resolution image from a set of low-resolution images captured with different illumination angles, which is susceptible to ambient noise, system noise, and weak currents when acquiring large-angle images, especially dark field images. To effectively address the noise problem, we propose an adaptive denoising algorithm based on a LED-based temporal variant noise model. Taking the results of blank slide samples as the reference value of noise, and analyzing the distribution of noise, we establish a statistical model for temporal variant noise, describing the relationship between temporal noise and LED spatial location.

Non-invasive accelerated imaging through a scattering medium via multi-stage complexity guidance.

The research of scattering imaging is of great significance to the development of various fields, but the existing scattering imaging methods are difficult to combine for the advantages of non-invasiveness, real-time imaging, and high quality. In this paper, a new, to our knowledge, scattering imaging technique is proposed that optimizes the traditional autocorrelation imaging technique by multi-stage complexity guidance and the initial acceleration module. We introduce the complexity difference index into the phase iterative recovery step for effective complexity guidance, and add the initial module based on error-reduction iteration to realize a fast startup.

Super-resolution imaging through scattering media based on improved triple correlation recursion and deterministic iterative estimation.

Iterative phase retrieval algorithms are commonly used in computational techniques and optimization methods to obtain the reconstruction of objects hidden behind opaque scattering media. However, these methods are susceptible to converging to incorrect local minima, and the calculation results tend to be unstable. In this paper, a triple-correlation-based super-resolution imaging (TCSI) framework is proposed to achieve single-shot imaging of unknown objects hidden behind the scattering medium.

Self-Modulated Ghost Imaging in Dynamic Scattering Media.

In this paper, self-modulated ghost imaging (SMGI) in a surrounded scattering medium is proposed. Different from traditional ghost imaging, SMGI can take advantage of the dynamic scattering medium that originally affects the imaging quality and generate pseudo-thermal light through the dynamic scattering of free particles' Brownian motion in the scattering environment for imaging. Theoretical analysis and simulation were used to establish the relationship between imaging quality and particle concentration.

Dual-camera compressive hyperspectral imaging based on deep image prior and a guided filter.

Coded aperture snapshot spectral imaging (CASSI) aims to capture the high-dimensional (usually 3D) data cube using a 2D sensor in a single snapshot. Due to the ill-posed snapshot, the reconstruction results are not ideal. One feasible solution is to utilize additional information such as the panchromatic measurement in CASSI.

Image dehazing algorithm based on optimized dark channel and haze-line priors of adaptive sky segmentation.

When dealing with outdoor hazy images, traditional image dehazing algorithms are often affected by the sky regions, resulting in appearing color distortions and detail loss in the restored image. Therefore, we proposed an optimized dark channel and haze-line priors method based on adaptive sky segmentation to improve the quality of dehazed images including sky areas. The proposed algorithm segmented the sky region of a hazy image by using the Gaussian fitting curve and prior information of sky color rules to calculate the adaptive threshold.

Multi-angle lensless ptychographic imaging via adaptive correction and the Nesterov method.

Lensless systems based on ptychographic imaging can simultaneously achieve a large field of view and high resolution while having the advantages of small size, portability, and low cost compared to traditional lensed imaging. However, lensless imaging systems are susceptible to environmental noise and have a lower resolution of individual images than lens-based imaging systems, which means that they require a longer time to obtain a good result. Therefore, in this paper, to improve the convergence rate and robustness of noise in lensless ptychographic imaging, we propose an adaptive correction method, in which we add an adaptive error term and noise correction term in lensless ptychographic algorithms to reach convergence faster and create a better suppression effect on both Gaussian noise and Poisson noise.

Efficient multiplexed illumination and imaging approach for Fourier ptychographic microscopy.

A Fourier ptychographic microscope (FPM) can obtain images with high resolution and a wide field of view (FOV). However, the time-consuming process of image acquisition and computation leads to low reconstruction efficiency. Therefore, we propose a state-multiplexed method through an optimized illumination pattern to accelerate FPM.

Parameter Estimation of Poisson-Gaussian Signal-Dependent Noise from Single Image of CMOS/CCD Image Sensor Using Local Binary Cyclic Jumping.

Since signal-dependent noise in a local weak texture region of a noisy image is approximated as additive noise, the corresponding noise parameters can be estimated from a given set of weakly textured image blocks. As a result, the meticulous selection of weakly textured image blocks plays a decisive role to estimate the noise parameters accurately. The existing methods consider the finite directions of the texture of image blocks or directly use the average value of an image block to select the weakly textured image block, which can result in errors.

An efficient Fourier ptychographic microscopy method based on optimized pattern of LED angle illumination.

Considering angle diversity and synthetic aperture, Fourier ptychographic microscopy (FPM) could address contradiction of high resolution and wide field of view. However, in the conventional FPM method, large capture quantity leads to poor efficiency. So, an efficient FPM method based on optimized pattern of LED angle illumination is proposed.

Fine-time measurement circuit based on 180° phase-shifted clock sampling in time-to-digital converters.

Dead time is an important parameter in time-to-digital converters, which is the significant time measure circuit. To reduce the dead time, this note proposes a new fine-time measurement circuit. In this configuration, two clocks having a phase difference of 180° are used to sample the signals passing through the delay chain, and their average is taken as the final measurement result.

Microscopic imaging quality improvement through L0 gradient constraint model based on multi-fields of view analysis.

The degradation of optical microscopic imaging is space-variant, and how to fast restore optical degraded image remains a special problem. Based on point spread function (PSF) estimation under each field of view (FOV), a L0 gradient-constrained image restoration method is proposed to solve optical degradation in microscopic imaging. Firstly, the whole scene is segmented into several different regions according to different FOV.