Improve Image Contrast Research Articles

Single-objective selective-volume illumination microscopy enables high-contrast light-field imaging.

The performance of light-field microscopy is improved by selectively illuminating the relevant subvolume of the specimen with a second objective lens. Here we advance this approach to a single-objective geometry, using an oblique one-photon illumination path or two-photon illumination to accomplish selective-volume excitation. The elimination of the second orthogonally oriented objective to selectively excite the volume of interest simplifies specimen mounting; yet, this single-objective approach still reduces the out-of-volume background, resulting in improvements in image contrast, effective resolution, and volume reconstruction quality. We validate our new, to the best of our knowledge, approach through imaging live developing zebrafish, demonstrating the technology's ability to capture imaging data from large volumes synchronously with high contrast while remaining compatible with standard microscope sample mounting.

Biomarkers in Pancreatic Cancer as Analytic Targets for Nanomediated Imaging and Therapy.

As the increase in therapeutic and imaging technologies is swiftly improving survival chances for cancer patients, pancreatic cancer (PC) still has a grim prognosis and a rising incidence. Practically everything distinguishing for this type of malignancy makes it challenging to treat: no approved method for early detection, extended asymptomatic state, limited treatment options, poor chemotherapy response and dense tumor stroma that impedes drug delivery. We provide a narrative review of our main findings in the field of nanoparticle directed treatment for PC, with a focus on biomarker targeted delivery. By reducing drug toxicity, increasing their tumor accumulation, ability to modulate tumor microenvironment and even improve imaging contrast, it seems that nanotechnology may one day give hope for better outcome in pancreatic cancer. Further conjugating nanoparticles with biomarkers that are overexpressed amplifies the benefits mentioned, with potential increase in survival and treatment response.

Novel FAP ligands enable improved imaging contrast in sarcoma patients due to FAPI-PET/CT

PurposeA high expression of fibroblast activation protein (FAP) was observed in multiple sarcomas, indicating an enormous potential for PET/CT using 68Ga-radiolabeled inhibitors of FAP (FAPI). Therefore, this retrospective study aimed to evaluate the role of the novel hybrid imaging probe for sarcomas as a first clinical evaluation.MethodsA cohort of 15 patients underwent 68Ga-FAPI-PET/CT for staging or restaging. The acquisition of PET scans was performed 60 min after administration of 127 to 308 MBq of the tracer. The uptake of 68Ga-FAPI in malignant tissue as well as in healthy organs was quantified by standardized uptake values SUVmean and SUVmax.ResultsExcellent tumor-to-background ratios (> 7) could be achieved due to low background activity and high SUVmax in primary tumors (median 7.16), local relapses (median 11.47), and metastases (median 6.29). The highest uptake was found for liposarcomas and high-grade disease (range 18.86–33.61). A high SUVmax (> 10) was observed for clinically more aggressive disease.ConclusionThese preliminary findings suggest a high potential for the clinical use of 68Ga-FAPI-PET/CT for patients diagnosed with sarcoma.

PET image reconstruction with deep progressive learning

Convolutional neural networks (CNNs) have recently achieved state-of-the-art results for positron emission tomography (PET) imaging problems. However direct learning from input image to target image is challenging if the gap is large between two images. Previous studies have shown that CNN can reduce image noise, but it can also degrade contrast recovery for small lesions. In this work, a deep progressive learning (DPL) method for PET image reconstruction is proposed to reduce background noise and improve image contrast. DPL bridges the gap between low quality image and high quality image through two learning steps. In the iterative reconstruction process, two pre-trained neural networks are introduced to control the image noise and contrast in turn. The feedback structure is adopted in the network design, which greatly reduces the parameters. The training data come from uEXPLORER, the world’s first total-body PET scanner, in which the PET images show high contrast and very low image noise. We conducted extensive phantom and patient studies to test the algorithm for PET image quality improvement. The experimental results show that DPL is promising for reducing noise and improving contrast of PET images. Moreover, the proposed method has sufficient versatility to solve various imaging and image processing problems.

P‐111: Halo guides the design of backlight partition in Mini‐LED Display

Applying high dynamic range(HDR) to mini‐LED backlight is the current research interest of display. The partition control technology for backlight of mini LED is adopted to improve image contrast, however it can not avoid the introduction of halo, which affects the image quality and needs to be solved. Therefore, this article firstly proposes a method to evaluate halo; Then we studied the brightness distribution of the halo from the perspective of the backlight and the module. We also put forward some factors that affect the size of the halo. It is hoped that the design of backlight partitions can be guided through the study of halo.

Respiratory motion correction for enhanced quantification of hepatic lesions in simultaneous PET and DCE-MR imaging

Simultaneous positron-emission tomography (PET)-magnetic resonance (MR) imaging is a hybrid technique in oncological hepatic imaging combining soft-tissue and functional contrast of dynamic contrast enhanced MR (DCE-MR) with metabolic information from PET. In this context, respiratory motion represents a major challenge by introducing blurring, artifacts and misregistration in the liver. In this work, we propose a free-breathing 3D non-rigid respiratory motion correction framework for simultaneously acquired DCE-MR and PET data, which makes use of higher spatial resolution MR data to derive motion information used directly during image reconstruction to minimize image blurring and motion artifacts. The main aim was to increase contrast of hepatic metastases to improve their detection and characterization. DCE-MR data were acquired at 3T through a golden radial phase encoding scheme, enabling derivation of motion fields. These were used in the motion compensated image reconstruction of DCE-MR time-series (48 time-points, 6 s temporal resolution, 1.5 mm isotropic spatial resolution) and 3D PET activity map, which was subsequently interpolated to the DCE-MR resolution. The extended Tofts model was fitted to DCE-MR data, obtaining functional parametric maps related to perfusion such as the endothelial permeability (). Fifty-seven hepatic metastases were identified and analyzed. Quantitative evaluations of motion correction in PET images demonstrated average percentage increases of 16% ± 5% (mean ± SD) in Contrast (C), 18% ± 6% in SUVmean and 14% ± 2% in SUVmax, while DCE-MR and scored contrast-to-noise-ratio increases of 64% ± 3% and 90% ± 6%, respectively. Motion-corrected data visually showed improved image contrast of hepatic metastases and effectively reduced blurring and motion artefacts. Scatter plots of SUVmean versus suggested that the proposed framework improved differentiation of measurements. The presented motion correction framework for simultaneously acquired PET-DCE-MR data provides accurately aligned images with increased contrast of hepatic lesions allowing for improved detection and characterization.

Optimal phase shift mask and multilayer stack with the evaluation of imaging performance and process latitude in extreme ultraviolet high numerical aperture

In high numerical aperture (NA) extreme ultraviolet lithography, which is used to implement a finer linewidth of 10 nm or lower, serious problems arise in patterning as the NA increases. To alleviate such problems, a thin absorber and a multilayer with good reflective efficiency and improved pattern quality are required. To develop an effective EUV photomask for the commercialization of high-NA systems, we determined the optimal ruthenium (Ru)/silicon (Si) multilayer structure using a phase-shift mask (PSM) absorber. A Ru/Si multilayer using PSM as an absorber has a smaller best-focus range and placement error compared to the molybdenum (Mo)/silicon (Si) multilayer. At the same time, it provides improved image contrast, enabling more stable patterning. Even when the number of layers of the Ru/Si multilayer was reduced, it was confirmed that the reflectance efficiency and image quality were maintained.

Evaluating a new generation of wearable high-density diffuse optical tomography technology via retinotopic mapping of the adult visual cortex.

Significance: High-density diffuse optical tomography (HD-DOT) has been shown to approach the resolution and localization accuracy of blood oxygen level dependent-functional magnetic resonance imaging in the adult brain by exploiting densely spaced, overlapping samples of the probed tissue volume, but the technique has to date required large and cumbersome optical fiber arrays.Aim: To evaluate a wearable HD-DOT system that provides a comparable sampling density to large, fiber-based HD-DOT systems, but with vastly improved ergonomics.Approach: We investigated the performance of this system by replicating a series of classic visual stimulation paradigms, carried out in one highly sampled participant during 15 sessions to assess imaging performance and repeatability.Results: Hemodynamic response functions and cortical activation maps replicate the results obtained with larger fiber-based systems. Our results demonstrate focal activations in both oxyhemoglobin and deoxyhemoglobin with a high degree of repeatability observed across all sessions. A comparison with a simulated low-density array explicitly demonstrates the improvements in spatial localization, resolution, repeatability, and image contrast that can be obtained with this high-density technology.Conclusions: The system offers the possibility for minimally constrained, spatially resolved functional imaging of the human brain in almost any environment and holds particular promise in enabling neuroscience applications outside of the laboratory setting. It also opens up new opportunities to investigate populations unsuited to traditional imaging technologies.

Rational Linker Design to Accelerate Excretion and Reduce Background Uptake of Peptidomimetic PSMA-Targeting Hybrid Molecules.

The evolution of peptidomimetic hybrid molecules for preoperative imaging and guided surgery targeting the prostate-specific membrane antigen (PSMA) significantly progressed over the past few years, and some approaches are currently being evaluated for further clinical translation. However, accumulation in nonmalignant tissue such as kidney, bladder, spleen, or liver might limit tumor-to-background contrast for precise lesion delineation, particularly in a surgical setting. To overcome these limitations, a rational linker design aims at the development of a second generation of PSMA-11-based hybrid molecules with an enhanced pharmacokinetic profile and improved imaging contrast. Methods: A selection of rationally designed linkers was introduced to the PSMA-targeting hybrid molecule Glu-urea-Lys-HBED-CC-IRDye800CW, resulting in a second-generation peptidomimetic hybrid molecule library. The biologic properties were investigated in cell-based assays. In a preclinical proof-of-concept study with the radionuclide 68Ga, the impact of the modifications was evaluated by determination of specific tumor uptake, pharmacokinetics, and fluorescence imaging in tumor-bearing mice. Results: The modified hybrid molecules carrying various selected linkers revealed high PSMA-specific binding affinity and effective internalization. The highest tumor-to-background contrast of all modifications investigated was identified for the introduction of a histidine- (H) and glutamic acid (E)-containing linker ((HE)3-linker) between the PSMA-binding motif and the chelator. In comparison to the parental core structure, uptake in nonmalignant tissue was significantly reduced to a minimum, as exemplified by an 11-fold reduced spleen uptake from 38.12 ± 14.62 percentage injected dose (%ID)/g to 3.47 ± 1.39 %ID/g (1 h after injection). The specific tumor uptake of this compound (7.59 ± 0.95 %ID/g, 1 h after injection) was detected to be significantly higher than that of the parental tracer PSMA-11. These findings confirmed by PET and fluorescence imaging are accompanied by an enhanced pharmacokinetic profile with accelerated background clearance at early time points after injection. Conclusion: The novel generation of PSMA-targeting hybrid molecules reveals fast elimination, reduced background organ enrichment, and high PSMA-specific tumor uptake meeting the key demands for potent tracers in nuclear medicine and fluorescence-guided surgery. The approach's efficacy in improving the pharmacokinetic profile highlights the strengths of rational linker design as a powerful tool in strategic hybrid-molecule development.

Artificial multisensory integration nervous system with haptic and iconic perception behaviors

Sensory neurons integrate multiple sensory inputs into a synthetical perception to monitor complex environments, which significantly impact on how we perceive the world. However, a true implementation of such an electronic device to mimic multiple sensory modalities, especially the coordinating behaviors of multisensory integration, has rarely been reported thus far. Herein, an artificial multisensory integration nervous system with haptic and iconic perception behaviors is developed by integrating flexible triboelectric nanogenerator (TENG) with organic photosynaptic transistor, where lead-free perovskite (Cs 2 AgBiBr 6 ) quantum dots (QDs) are firstly presented. Meanwhile, Inverse effectiveness effect and Temporal congruency, which are the primary principles of multisensory integration in biological perceptual system, are firstly precisely mimicked in our system. Moreover, the pattern recognition results show that multisensory integration exhibited obviously higher accuracy than single sense, which is consistent with biological system. Furthermore, 3 × 3 pixel array of artificial photosynaptic circuits actuated with TENG is designed and demonstrated for the recognition of various objects in extreme environments, which further verifies the superiority of the multisensory integration with improved image contrast, accuracy of subsequent pattern recognition, and environment-adaptable perception behaviors. This work provides new insight into developing artificial multisensory integration nerve in neuromorphic perceptions and neuromorphic computing, which is of great significance in future human-machine interaction, sophisticated robotic prostheses and neurorobotic system. • Lead-free perovskite (Cs 2 AgBiBr 6 ) quantum dots (QDs) are firstly synthesized for artificial neuromorphic sensory system. • Artificial multisensory integration perceptual system is firstly presented by integrating organic photosynaptic transistor with a triboelectric nanogenerator. • 3 × 3 pixel array of artificial photosynaptic circuits actuated with TENG is demonstrated for the recognition of various objects in extreme environments, which further verifies the superiority of the multisensory integration with improved accuracy of pattern recognition and environment-adaptable perception behaviors.

Recent Progress in Nanomedicine for Melanoma Theranostics With Emphasis on Combination Therapy.

Melanoma is an aggressive type of skin cancer with increasing incidence and high mortality rates worldwide. However, there is still a lack of efficient and resolutive treatment strategies, particularly in clinical settings. Currently, nanomedicine, an emerging area in the medical field, is being widely investigated in small animal models to afford melanoma theranostics. However, several problems, such as tumor heterogeneity, and drug resistance treatment with a single therapy, remain unresolved. Previous reviews have primarily focused on monotherapy for melanoma in the context of nanomedicine. In this review article, we summarize the recent progress in the application of nanomedicine for melanoma treatment, with particular attention to combination therapy based on nanomedicine to achieve optimized therapeutic output for melanoma treatment. In addition, we also highlight the fluorescence-guided strategies for intraoperative melanoma detection, especially in the near-infrared imaging window with greatly improved imaging contrast and penetration depth.

Fast OCT image enhancement method based on the sigmoid-energy conservation equation.

Optical coherence tomography (OCT) is an important medical diagnosis technology, but OCT images are inevitably interfered by speckle noise and other factors, which greatly reduce the quality of the OCT image. In order to improve the quality of the OCT image quickly, a fast OCT image enhancement method is proposed based on the fusion equation. The proposed method consists of three parts: edge detection, noise suppression, and image fusion. In this paper, the improved wave algorithm is used to detect the image edge and its fine features, and the averaging uncorrelated images method is used to suppress speckle noise and improve image contrast. In order to sharpen image edges while suppressing the speckle noise, a sigmoid-energy conservation equation (SE equation) is designed to fuse the edge detection image and the noise suppression image. The proposed method was tested on two publicly available datasets. Results show that the proposed method can effectively improve image contrast and sharpen image edges while suppressing the speckle noise. Compared with other state-of-the-art methods, the proposed method has better image enhancement effect and speed. Under the same or better enhancement effect, the processing speed of the proposed method is 2 ∼ 34 times faster than other methods.

Spatial-frequency-based image reconstruction to improve image contrast in multi-offset adaptive optics ophthalmoscopy.

Off-axis detection methods in adaptive optics (AO) ophthalmoscopy can enhance image contrast of translucent retinal structures such as cone inner segments and retinal ganglion cells. Here, we propose a 2D optical model showing that the phase contrast produced by these methods depends on the offset orientation. While one axis provides an asymmetric light distribution, hence high phase contrast, the perpendicular axis provides a symmetric one, thus substantially lower contrast. We support this model with in vivo human data acquired with a multi-offset AO scanning light ophthalmoscope. Then, using this finding, we provide a post-processing method, named spatial-frequency-based image reconstruction, to optimally combine images from different off-axis detector orientations, significantly increasing the structural cellular contrast of in vivo human retinal neurons such as cone inner segment, putative rods, and retinal ganglion cells.

Layout Classification of Red Onion Disease on Onion Leaf Image Using Artificial Neural Network

Shallots are one of the main ingredients that are often found throughout Indonesia. The optimal yield of onion plants is influenced by several factors, one of which is disease. The purpose of this study is to classify the image of leeks to identify onion diseases using Artificial Neural Network (ANN). Disease classification on leeks is leaf rot (anthracnose) and purple spots. The steps taken in the classification of leek disease are data input, pre-processing, feature extraction, machine learning. Several steps are carried out on the leek image, among others, improving image contrast, conversion of sRGB to LAB, segmentation using clustering, grayscale images, and binary images. After pre-processing, the next step is extracting features based on colour features and texture features. The colour features consist of Standard Deviation, Kurtosis, Mean, and Skewness. While the texture features consist of Contrast, Correlation, Energy, Entropy, Variance, and IDM. The end result of this system will show whether the leeks are included in the class of leaf rot (anthracnose) or purple spots or healthy leaves.

A Biologically Friendly, Low‐Cost, and Scalable Method to Map Permeable Media Architecture and Interstitial Flow

AbstractPorous media are ubiquitous, a key component of the water cycle and locus of many biogeochemical transformations. Mapping media architecture and interstitial flows have been challenging because of the inherent difficulty of seeing through solids. Previous works used particle image velocimetry (PIV) coupled with refractive index‐matching (RIM) to quantify interstitial flows, but they were limited to specialized and often toxic fluids that precluded investigating biological processes. To address this limitation, we present a low‐cost and scalable method based on RIM coupled PIV (RIM‐PIV) and planar laser induced fluorescence (RIM‐PLIF) to simultaneously map both media architecture and interstitial velocities. Our method uses irregularly shaped grains made of a fluorocarbon plastic with refractive index of 1.36 and specific gravity of 1.93. This allows using a water–glycerin solution for the RIM fluid. By using RIM‐PIV, we mapped media structure with 2% accuracy, which improved to 0.2% with RIM‐PLIF because of improved image contrast.

3D magnetization transfer (MT) for the visualization of cardiac free-running Purkinje fibers: an ex vivo proof of concept

ObjectivesWe investigate the possibility to exploit high-field MRI to acquire 3D images of Purkinje network which plays a crucial role in cardiac function. Since Purkinje fibers (PF) have a distinct cellular structure and are surrounded by connective tissue, we investigated conventional contrast mechanisms along with the magnetization transfer (MT) imaging technique to improve image contrast between ventricular structures of differing macromolecular content.MethodsThree fixed porcine ventricular samples were used with free-running PFs on the endocardium. T1, T2*, T2, and M0 were evaluated on 2D slices for each sample at 9.4 T. MT parameters were optimized using hard pulses with different amplitudes, offset frequencies and durations. The cardiac structure was assessed through 2D and 3D T1w images with isotropic resolutions of 150 µm. Histology, immunofluorescence, and qPCR were performed to analyze collagen contents of cardiac tissue and PF.ResultsAn MT preparation module of 350 ms duration inserted into the sequence with a B1 = 10 µT and frequency offset = 3000 Hz showed the best contrast, approximately 0.4 between PFs and myocardium. Magnetization transfer ratio (MTR) appeared higher in the cardiac tissue (MTR = 44.7 ± 3.5%) than in the PFs (MTR = 25.2 ± 6.3%).DiscussionMT significantly improves contrast between PFs and ventricular myocardium and appears promising for imaging the 3D architecture of the Purkinje network.

A Self-Assembling and Disassembling (SADA) Bispecific Antibody (BsAb) Platform for Curative Two-step Pretargeted Radioimmunotherapy.

Many cancer treatments suffer from dose-limiting toxicities to vital organs due to poor therapeutic indices. To overcome these challenges we developed a novel multimerization platform that rapidly removes tumor-targeting proteins from the blood to substantially improve therapeutic index. The platform was designed as a fusion of a self-assembling and disassembling (SADA) domain to a tandem single-chain bispecific antibody (BsAb, anti-ganglioside GD2 × anti-DOTA). SADA-BsAbs were assessed with multiple in vivo tumor models using two-step pretargeted radioimmunotherapy (PRIT) to evaluate tumor uptake, dosimetry, and antitumor responses. SADA-BsAbs self-assembled into stable tetramers (220 kDa), but could also disassemble into dimers or monomers (55 kDa) that rapidly cleared via renal filtration and substantially reduced immunogenicity in mice. When used with rapidly clearing DOTA-caged PET isotopes, SADA-BsAbs demonstrated accurate tumor localization, dosimetry, and improved imaging contrast by PET/CT. When combined with therapeutic isotopes, two-step SADA-PRIT safely delivered massive doses of alpha-emitting (225Ac, 1.48 MBq/kg) or beta-emitting (177Lu, 6,660 MBq/kg) S-2-(4-aminobenzyl)-1,4,7,10-tetraazacyclododecane tetraacetic acid (DOTA) payloads to tumors, ablating them without any short-term or long-term toxicities to the bone marrow, kidneys, or liver. The SADA-BsAb platform safely delivered large doses of radioisotopes to tumors and demonstrated no toxicities to the bone marrow, kidneys, or liver. Because of its modularity, SADA-BsAbs can be easily adapted to most tumor antigens, tumor types, or drug delivery approaches to improve therapeutic index and maximize the delivered dose.See related commentary by Capala and Kunos, p. 377.

Image Contrast Improvement in Image Fusion between CT and MRI images of Brain Cancer Patients

Medical image fusion has been carried out to obtain information benefits from multi-modalities of medical images. The purpose of this study is to improve the image contrast of fusion image with adaptive method. The median filter was implemented to the images before registration to remove noise for obtaining good image fusion. Geometric transformation-based image registration was used to automatically align two images of computed tomography (CT) scanner and magnetic resonance imaging (MRI) to a common coordinate system. After that, the image contrast was improved with adaptive method. Finally, the fused image was assessed using the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). From this study, it was found that the average SNR value in the image fusion before contrast improvement is 0.09 and after that is 0.73. While the average CNR value in image fusion before contrast improvement is 1.54 and after that is 1.79. It means that the CNR increases 14.02%.

Towards practical implementation of the compressed sensing framework for multi-element synthetic transmit aperture imaging

Compressed sensing (CS) has been adapted to synthetic aperture (SA) ultrasound imaging to improve the frame-rate of the system. Recently, we proposed a novel CS framework using Gaussian under-sampling to reduce the number of receive elements in multi-element synthetic transmit aperture (MSTA) imaging. However, that framework requires different receive elements to be chosen randomly for each transmission, which may add to practical implementation challenges. Modifying the scheme to employ the same set of receive elements for all transmissions of MSTA leads to degradation of the recovered image quality. Therefore, this work proposes a novel sampling scheme based on a genetic algorithm (GA), which optimally chooses the receive element positions once and uses it for all the transmission of MSTA. The CS performance using GA sampling schemes is evaluated against the previously proposed CS framework on in-vitro and in-vivo datasets. The obtained results suggest that not only does the GA-based approach allows the use of the same set of sparse receive elements for each transmit, but also leads to the lowest CS recovery error (NRMSE) and 14% overall improvement in image contrast, in comparison to the previously-proposed Gaussian sampling scheme. Thus, using the CS framework along with GA, can potentially reduce the complexity in implementation of CS-framework to MSTA based systems.

A Pulse-Number-Adjustable MSPCNN and Its Image Enhancement Application

Pulse-coupled neural network (PCNN) aims to control neuronal firing state automatically and complete related image processing tasks. This paper presents a pulse-number-adjustable MSPCNN model (PNA-MSPCNN) that can automatically acquire the firing times and the firing frequency of each neuron. Hereinto, synaptic weight matrix Wijkl and decay factor α will generate an interaction value to determine the final calculation result of the internal activity U. Dynamic threshold amplitude V, step function Q, and auxiliary parameter P can precisely adjust the variation ranges of the dynamic threshold E. Additionally, we propose a low-light image enhancement method based on the above PNA-MSPCNN and a modified low-light image enhancement (LIME). The proposed LIME algorithm focuses mainly on the parameter setting method of weight matrix Wmq, which will bring further improvement of testing image contrast. Experimental results demonstrate that our proposed method achieves better low-light image enhancement performances, compared to prevalent image enhancement methods, including SSIM of 0.8725, AMBE of 0.0550, MSE of 0.0092, and PSNR of 45.7764.