Improve Image Contrast Research Articles

Improved susceptibility-weighted imaging for high contrast and resolution thalamic nuclei mapping at 7T.

The thalamus is an important brain structure and neurosurgical target, but its constituting nuclei are challenging to image non-invasively. Recently, susceptibility-weighted imaging (SWI) at ultra-high field has shown promising capabilities for thalamic nuclei mapping. In this work, several methodological improvements were explored to enhance SWI quality and contrast, and specifically its ability for thalamic imaging. High-resolution SWI was performed at 7T in healthy participants, and the following techniques were applied: (a) monitoring and retrospective correction of head motion and B0 perturbations using integrated MR navigators, (b) segmentation and removal of venous vessels on the SWI data using vessel enhancement filtering, and (c) contrast enhancement by tuning the parameters of the SWI phase-magnitude combination. The resulting improvements were evaluated with quantitative metrics of image quality, and by comparison to anatomo-histological thalamic atlases. Even with sub-millimeter motion and natural breathing, motion and field correction produced clear improvements in both magnitude and phase data quality (76% and 41%, respectively). The improvements were stronger in cases of larger motion/field deviations, mitigating the dependence of image quality on subject performance. Optimizing the SWI phase-magnitude combination yielded substantial improvements in image contrast, particularly in the thalamus, well beyond previously reported SWI results. The atlas comparisons provided compelling evidence of anatomical correspondence between SWI features and several thalamic nuclei, for example, the ventral intermediate nucleus. Vein detection performed favorably inside the thalamus, and vein removal further improved visualization. Altogether, the proposed developments substantially improve high-resolution SWI, particularly for thalamic nuclei imaging.

Image Enhancement using Recursive Separate Standard Intensity Deviation Based Clipped Sub Image Histogram Equalization

To improve image contrast, this paper introduces a recursive separate standard intensity deviation based clipped sub image histogram equalization method. This is an extension of standard intensity deviation value based sub image histogram equalization algorithm, in terms of histogram separation and equalization. In existing equalization methods do not effectively utilizes the information from different region in equalization process. In this scheme, the image histogram is bisected based on standard intensity deviation value. The further separation is carried out based on the specific region threshold value and the resulting four sub histograms are equalized individually. This is an effective method for enhancing, low exposure, medical and mammogram images and for addressing the over-enhancement problem. The performance evaluation of the proposed method is presented with the help of average information and visual quality assessment and the proposed algorithm outperforms existing recursive algorithms based on histogram equalization.

Enhancement of soft-tissue contrast in cone-beam CT using an anti-scatter grid with a sparse sampling approach

PurposeAnti-scatter grids suppress the scatter substantially thus improving image contrast in radiography. However, its active use in cone-beam CT for the purpose of improving contrast-to-noise ratio (CNR) has not been successful mainly due to the increased noise related to Poisson statistics of photons. This paper proposes a sparse-view scanning approach to address the above issue. MethodCompared to the conventional cone-beam CT imaging framework, the proposed method reduces the number of projections and increases exposure in each projection to enhance image quality without an additional cost of radiation dose to patients. For image reconstruction from sparse-view data, an adaptive-steepest-descent projection-onto-convex-sets (ASD POCS) algorithm regularized by total-variation (TV) minimization was adopted. Contrast and CNR with various scattering conditions were evaluated in projection domain by a simulation study using GATE. Then we evaluated contrast, resolution, and image uniformity in CT image domain with Catphan phantom. A head phantom with soft-tissue structures was also employed for demonstrating a realistic application. A virtual grid-based estimation and reduction of scatter has also been implemented for comparison with the real anti-scatter grid. ResultsIn the projection domain evaluation, contrast and CNR enhancement was observed when using an anti-scatter grid compared to the virtual grid. In the CT image domain, the proposed method produced substantially higher contrast and CNR of the low-contrast structures with much improved image uniformity. ConclusionWe have shown that the proposed method can provide high-quality CBCT images particularly with an increased contrast of soft-tissue at a neutral dose for image-guidance.

Mapping 2D- and 3D-distributions of metal/metal oxide nanoparticles within cleared human ex vivo skin tissues

Increasing numbers of commercial skincare products are being manufactured with engineered nanomaterials (ENMs), prompting a need to fully understand how ENMs interact with the dermal barrier as a major biodistribution entry route. Although animal studies show that certain nanomaterials can cross the skin barrier, physiological differences between human and animal skin, such as the lack of sweat glands, limit the translational validity of these results. Current optical microscopy methods have limited capabilities to visualize ENMs within human skin tissues due to the high amount of background light scattering caused by the dense, ubiquitous extracellular matrix (ECM) of the skin. Here, we hypothesized that organic solvent-based tissue clearing (“immunolabeling-enabled three-dimensional imaging of solvent-cleared organs”, or “iDISCO”) would reduce background light scattering from the extracellular matrix of the skin to sufficiently improve imaging contrast for both 2D mapping of unlabeled metal oxide ENMs and 3D mapping of fluorescent nanoparticles. We successfully mapped the 2D distribution of label-free TiO2 and ZnO nanoparticles in cleared skin sections using correlated signals from darkfield, brightfield, and confocal microscopy, as well as micro-spectroscopy. Specifically, hyperspectral microscopy and Raman spectroscopy confirmed the identity of label-free ENMs which we mapped within human skin sections. We also measured the 3D distribution of fluorescently labeled Ag nanoparticles in cleared skin biopsies with wounded epidermal layers using light sheet fluorescence microscopy. Overall, this study explores a novel strategy for quantitatively mapping ENM distributions in cleared ex vivo human skin tissue models using multiple imaging modalities. By improving the imaging contrast, we present label-free 2D ENM tracking and 3D ENM mapping as promising capabilities for nanotoxicology investigations.

An Enhanced Image Fusion Algorithm by Combined Histogram Equalization and Fast Gray Level Grouping Using Multi-Scale Decomposition and Gray-PCA

Image enhancement is a challenging task in image analysis particularly, it is more challenging in performing image fusion. Image fusion is the process of combining multiple images to produce quality output without any variation in contrast, blurring, and noise. Many image fusion algorithms have been implemented, but their final fused images suffer from variations in background contrast, uneven illumination, blurring, and the presence of noise. To overcome the aforementioned issues, this paper proposed a new image fusion method, which improves image contrast and also gives appropriate details of the image. Our method is based on a set of conventional techniques such as amalgamated histogram equalization and fast gray-scale grouping to handle the problems mentioned, and we improve overall fusion strategies by proposing a novel principal component analysis technique to convert RGB types images to high gray-scale contrast image as the final output image. We have carried out many experiments on different common databases used by various researchers. Our proposed method gives good subjective and objective performances compared to other statuses. Our proposed method can be used in different monitoring applications.

水下二维及三维距离选通成像去噪技术研究

Compared with traditional underwater cameras, the detection distance of underwater range-gated imaging can be increased by 2-3 times. Furthermore, based on this technology, fast high-resolution 3D imaging can be achieved. It has great potentials in underwater target detection and recognition, automatic navigation, marine scientific research and natural resources exploration. Although range-gated imaging can suppress the backscattering noise by space slicing, and achieve higher quality images, the backscattering noise of the sampling water volume still exists in gated images, resulting in low image signal-to-noise ratio and contrast, especially for distant targets or low reflectance targets. This paper systematically introduced author's research of deblurring methods for 2D and 3D range-gated imaging. In 2D imaging, two methods were proposed:the first was an algorithm of self-adaptive double-plateau histogram equalization to improve image contrast and better meet human vision; the second was to use a water-noise-reference denoising algorithm to improve the signal-to-noise ratio of target gated images. In 3D imaging, there were also two methods proposed:one was to use the water-noise-reference denoising algorithm for 3D reconstruction, and the other was to use the threshold-dependent joint bilateral filter algorithm for enhancing 3D images. The four proposed methods can be used independently or in combination for denoising enhancement of underwater range gated imaging.

Hyperspectral image visualization with edge-preserving filtering and principal component analysis

In this paper, an edge-preserving filtering and principal component analysis (PCA)-based visualization method is proposed for hyperspectral images, in which both global and local image information of hyperspectral images (HSIs) are taken into account in the proposed visualization framework that consists of the following major steps. First, the band number of the original image is reduced with averaging-based image fusion (AIF). Then, the edge-preserving filtering is performed on the dimension reduced image so as to decompose it into two components, i.e., the base layers which contain the large-scale boundary information, and the detail layers which contain the mid- and small-scale edges and textures. Next, the base layers are fused with the principal component analysis method, and the detail layers are fused with the weighted sum method, in which the fusion weights are determined by the transform matrix of the base layers. Finally, the fused detail layers are enhanced with histogram equalization and combined with the fused base layers to visualize the hyperspectral image. Experimental results on four real hyperspectral data sets demonstrate that the proposed approach performs the best in improving image contrast and preserving the details. In addition, compared with seven state-of-the-art visualization methods, the quantitative metrics obtained by the proposed method on four data sets have been increased by 80.45%, 69.29%, 138.61%, and 23.21% on average in terms of separability of features (SF), standard deviation (SD), average gradient (AG), and entropy (EN).

Schlieren diagnostic for cinematic visualization of dense plasma jets at Alfvénic timescales

The manner in which magnetized plasma jets evolve remains key to better understanding the behavior of hydromagnetic systems and providing new insights into how they can be dynamically controlled. In this work, we present the underlying theory, apparatus, and optical features of a schlieren diagnostic capable of cinematically visualizing dense plasma jets. We identify the range of plasma density over which the diagnostic is sensitive and describe ways to further improve image contrast. This diagnostic features the unique ability to simultaneously resolve both the characteristic Alfvenic timescales and spatial flow features with continuous acquisition over the lifetime of a jet. We use this diagnostic to visualize the formation and evolution of hydromagnetic jets produced from a plasma gun device. Dynamic coherent flow features are identified and tracked over time throughout the evolutionary progression of plasma jets. Finally, the process by which these coherent features translate into perturbations of magnetized bow shocks is visualized.

Spectral Signatures of X-ray Scatter Using Energy-Resolving Photon-Counting Detectors.

Energy-resolving photon-counting detectors (PCDs) separate photons from a polychromatic X-ray source into a number of separate energy bins. This spectral information from PCDs would allow advancements in X-ray imaging, such as improving image contrast, quantitative imaging, and material identification and characterization. However, aspects like detector spectral distortions and scattered photons from the object can impede these advantages if left unaccounted for. Scattered X-ray photons act as noise in an image and reduce image contrast, thereby significantly hindering PCD utility. In this paper, we explore and outline several important characteristics of spectral X-ray scatter with examples of soft-material imaging (such as cancer imaging in mammography or explosives detection in airport security). Our results showed critical spectral signatures of scattered photons that depend on a few adjustable experimental factors. Additionally, energy bins over a large portion of the spectrum exhibit lower scatter-to-primary ratio in comparison to what would be expected when using a conventional energy-integrating detector. These important findings allow flexible choice of scatter-correction methods and energy-bin utilization when using PCDs. Our findings also propel the development of efficient spectral X-ray scatter correction methods for a wide range of PCD-based applications.

Partial Fourier reconstruction for improved resolution in 3D hyperpolarized 13 C EPI.

Asymmetric in-plane k-space sampling of EPI can reduce the minimum achievable TE in hyperpolarized with spectral-spatial radio frequency pulses, thereby reducing weighting and signal-losses. Partial Fourier image reconstruction exploits the approximate Hermitian symmetry of k-space data and can be applied to asymmetric data sets to synthesize unmeasured data. Here we tested whether the application of partial Fourier image reconstruction would improve spatial resolution from hyperpolarized [1- ]pyruvate scans in the human brain. Fifteen healthy control subjects were imaged using a volumetric dual-echo echo-planar imaging sequence with spectral-spatial radio frequency excitation. Images were reconstructed by zero-filling as well as with the partial Fourier reconstruction algorithm projection-on-convex-sets. Resulting images were quantitatively evaluated with a no-reference image quality assessment. The no-reference image sharpness metric agreed with perceived improvements in image resolution and contrast. The [1- ]lactate images benefitted most, followed by the [1- ]pyruvate images. The -bicarbonate images were improved by the smallest degree, likely owing to relatively lower SNR. Partial Fourier imaging and reconstruction were shown to improve the sharpness and contrast of human HP brain data and is a viable method for enhancing resolution.

Short-lag spatial coherence imaging with multi-line transmission to improve needle visibility in ultrasound images

Ultrasound Short Lag Spatial Coherence (SLSC) imaging exploits the spatial coherence (SC) of backscattered echoes to suppress acoustic clutter and to significantly improve image contrast, particularly in difficult-to-image patients. Multi-line transmission (MLT) imaging simultaneously transmits multiple beams to increase frame rates. We hypothesize that the combination of SLSC and MLT has the potential to enhance detectability of coherent structures within a tissue background. Sector images of a 14G biopsy needle inserted within ex vivo bovine meat were acquired after implementing single-line transmission (SLT) and MLT with 4, 6, 8 and 16 simultaneous beams. The SLSC algorithm was applied to the acquired data. Results show that MLT SLSC images have a visibly darker background than SLT SLSC images, which is caused by the rapid decorrelation of the SC at short lags with MLT. This decorrelation is caused by inter-beam crosstalk interferences and can be leveraged to enhance the coherence of highly reflective targets within a tissue background, causing an increase in needle contrast from about 25 dB with SLT to ∼44 dB with 16-MLT. These results support our hypothesis that the decorrelation caused by crosstalk improves visualization of highly coherent targets within tissue, with promising applications to biopsy needle localization.

Improved stability of a novel fluorine-18 labeled TCO analogue for pretargeted PET imaging

IntroductionBiorthogonal pretargeted imaging using the inverse electron demand Diels Alder (IEDDA) reaction between tetrazine (Tz) and trans-cyclooctene (TCO) is one of the most attractive strategies in molecular imaging. It allows the use of short-lived radioisotopes such as fluorine-18 for imaging of long circulating vectors with improved imaging contrast and reduced radiation dose. Here we aim to develop a novel 18F-labeled trans-cyclooctene (TCO) with improved metabolic stability and assess its potential usefulness in a pretargeted PET imaging approach. MethodsWe have synthetized a new TCO-analogue containing a 1,4,7-triazacyclononane-1,4,7-triacetic acid (NOTA) chelator, allowing radiolabeling by chelation with aluminum fluoride (Al[18F]F). Stability and pharmacokinetic profile of Al[18F]F-NOTA-TCO ([18F]MICA-205) were evaluated in healthy animals at different timepoints after injection of the radiotracer. To assess the potential use of this new PET tracer for tumor targeting, in vivo pretargeted PET imaging was performed in LS174T tumor-bearing mice pre-treated with a tetrazine-modified anti-TAG-72 monoclonal antibody (CC49). ResultsThe radiotracer was obtained with a radiochemical yield (RCY) of 12.8 ± 2.8% and a radiochemical purity (RCP) of ≥95%. It also showed a promising in vivo stability with 51.9 ± 5.16% of radiotracer remaining intact after 1 h. The biodistribution in healthy mice demonstrated mixed hepatobiliary and renal clearance, with a rapid blood clearance and low uptake in other tissues. The low bone uptake indicated lack of tracer defluorination. Interestingly, a pretargeted PET imaging experiment showed a significantly increased radiotracer uptake (0.67 ± 0.16%ID/g, p < 0.001) in the tumors of mice pre-treated with CC49-tetrazine compared to the CC49 alone (0.16 ± 0.08%ID/g). Conclusions[18F]MICA-205 represents a large improvement in in vivo metabolic stability compared to previous reported 18F-labeled TCOs, allowing a clear visualization of tumor tissue in a small-animal pretargeted PET imaging experiment. Despite the favorable in vivo stability and image contrast obtained with [18F]MICA-205, the development of next-generation derivatives with increased absolute tumor uptake is warranted for future pretargeting applications.

Image-contrast enhancement of wavefront coding systems by combining radially symmetrical phase and amplitude masks

The quartic phase mask is a radially symmetrical phase mask which is commonly used to analyze imaging performance and to apply in many practical applications. In this paper, we propose a simple, novel method to improve the image contrast for extending depth of field in wavefront coding system with radially symmetrical quartic phase mask. An amplitude mask, which improves image contrast in low spatial frequency region, is added on the wavefront coding system with quartic phase mask to obtain the remarkable improvement of imaging performance for extending depth of field. Some evaluation methods are used to show the effectiveness of imaging performance of the proposed method in comparison to previously phase mask. The results demonstrated that the proposed method yields better imaging property in extending depth of field.

Correcting versus resolving respiratory motion in free-breathing whole-heart MRA: a comparison in patients with thoracic aortic disease

BackgroundWhole-heart magnetic resonance angiography (MRA) requires sophisticated methods accounting for respiratory motion. Our purpose was to evaluate the image quality of compressed sensing-based respiratory motion-resolved three-dimensional (3D) whole-heart MRA compared with self-navigated motion-corrected whole-heart MRA in patients with known thoracic aorta dilation.MethodsTwenty-five patients were prospectively enrolled in this ethically approved study. Whole-heart 1.5-T MRA was acquired using a prototype 3D radial steady-state free-precession free-breathing sequence. The same data were reconstructed with a one-dimensional motion-correction algorithm (1D-MCA) and an extradimensional golden-angle radial sparse parallel reconstruction (XD-GRASP). Subjective image quality was scored and objective image quality was quantified (signal intensity ratio, SIR; vessel sharpness). Wilcoxon, McNemar, and paired t tests were used.ResultsSubjective image quality was significantly higher using XD-GRASP compared to 1D-MCA (median 4.5, interquartile range 4.5–5.0 versus 4.0 [2.25–4.75]; p < 0.001), as well as signal homogeneity (3.0 [3.0–3.0] versus 2.0 [2.0–3.0]; p = 0.003), and image sharpness (3.0 [2.0–3.0] vs 2.0 [1.25–3.0]; p < 0.001). SIR with the 1D-MCA and XD-GRASP was 6.1 ± 3.9 versus 7.4 ± 2.5, respectively (p < 0.001); while signal homogeneity was 274.2 ± 265.0 versus 199.8 ± 67.2 (p = 0.129). XD-GRASP provided a higher vessel sharpness (45.3 ± 10.7 versus 40.6 ± 101, p = 0.025).ConclusionsXD-GRASP-based motion-resolved reconstruction of free-breathing 3D whole-heart MRA datasets provides improved image contrast, sharpness, and signal homogeneity and seems to be a promising technique that overcomes some of the limitations of motion correction or respiratory navigator gating.

Quantitative dual-energy micro-CT with a photon-counting detector for material science and non-destructive testing.

The recent progress in photon-counting detector technology using high-Z semiconductor sensors provides new possibilities for spectral x-ray imaging. The benefits of the approach to extract spectral information directly from measurements in the projection domain are very advantageous for material science studies with x-rays as polychromatic artifacts like beam-hardening are handled properly. Since related methods require accurate knowledge of all energy-dependent system parameters, we utilize an adapted semi-empirical model, which relies on a simple calibration procedure. The method enables a projection-based decomposition of photon-counting raw-data into basis material projections. The objective of this paper is to investigate the method’s performance applied to x-ray micro-CT with special focus on applications in material science and non-destructive testing. Projection-based dual-energy micro-CT is shown to be of good quantitative accuracy regarding material properties such as electron densities and effective atomic numbers. Furthermore, we show that the proposed approach strongly reduces beam-hardening artifacts and improves image contrast at constant measurement time.

Head-to-head comparison of image quality between brain 18F-FDG images recorded with a fully digital versus a last-generation analog PET camera

BackgroundThe quality of phantom images was previously shown to be higher on digital (Vereos Philips®) compared to analog PET (Ingenuity Philips®) cameras. This study aimed to determine the extent to which this difference still remains significant on normal brain 18F-FDG PET images.MethodsRelative noise and contrast as well as border sharpness (a spatial resolution index) of central (striata) and peripheral (occiput) gray-matter structures were compared between 10 sets of normal brain 18F-FDG PET images recorded and reconstructed on digital and analog last-generation PET cameras, together with a subjective visual analysis of image quality provided by experienced physicians.ResultsCompared with analog PET, digital PET provided marked improvements in image quality parameters. The median relative noise was decreased (− 22%), while gray/white-matter contrast was increased (+ 27%/+ 41% for central/peripheral gray-matter structures), with these results being consistent with visual analysis. In addition, a clear enhancement in image sharpness was further documented for digital PET owing to the possible use of a 1-mm3 voxel size (+ 24%/+ 21%).ConclusionsOn normal brain 18F-FDG images and compared with a last-generation analog PET, the fully digital PET camera offers marked improvements in image noise and contrast, as well as significant potential for further enhancing spatial resolution.

Fast and accurate pseudo multispectral technique for whole-brain MRI tissue classification

Numerous strategies have been proposed to classify brain tissues into gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). However, many of them fail when classifying specific regions with low contrast between tissues. In this work, we propose an alternative pseudo multispectral classification (PMC) technique using CIE LAB spaces instead of gray scale T1-weighted MPRAGE images, combined with a new preprocessing technique for contrast enhancement and an optimized iterative K-means clustering. To improve the accuracy of the classification process, gray scale images were converted to multispectral CIE LAB data by applying several transformation matrices. Thus, the amount of information associated with each image voxel was increased. The image contrast was then enhanced by applying a real time function that separates brain tissue distributions and improve image contrast in certain brain regions. The data were then classified using an optimized iterative and convergent K-means classifier. The performance of the proposed approach was assessed using simulation and in vivo human studies through comparison with three common software packages used for brain MR image segmentation, namely FSL, SPM8 and K-means clustering. In the presence of high SNR, the results showed that the four algorithms achieve a good classification. Conversely, in the presence of low SNR, PMC was shown to outperform the other methods by accurately recovering all tissue volumes. The quantitative assessment of brain tissue classification for simulated studies showed that the PMC algorithm resulted in a mean Jaccard index (JI) of 0.74 compared to 0.75 for FSL, 0.7 for SPM and 0.8 for K-means. The in vivo human studies showed that the PMC algorithm resulted in a mean JI of 0.92, which reflects a good spatial overlap between segmented and actual volumes, compared to 0.84 for FSL, 0.78 for SPM and 0.66 for K-means. The proposed algorithm presents a high potential for improving the accuracy of automatic brain tissues classification and was found to be accurate even in the presence of high noise level.

Automatic Enhancement of Low Light Level Image on the Basis of a Gaussian Mixture Model

As the first medium to transmit information under a low light level environment. The low light level image is needed in hot-light image imaging technology. The quality of the image will be reduced given the influence of external factors. For example, a sampled image may become blurry. This paper proposes a method for automatic enhancement of low light level image on the basis of a Gaussian mixture model. First, the histogram of the image is modeled with a Gaussian mixture model that is solved by the expectation maximization algorithm of accelerated convergence. The histogram is then partitioned according to the intersection of each cluster. Finally, the mapping relationship of the cluster to which the output image belongs is ascertained and the final enhancement image is obtained. This algorithm can be used to identify the optimal number of clusters and accelerate the convergence speed of the algorithm. Objective evaluation of the Laplace operator value, as well as the grayscale average gradient and contrast (Tab. 1), indicates that the algorithm effectively improves image contrast while maintaining the details of the image.

Clinical Results in Medullary Thyroid Carcinoma Suggest High Potential of Pretargeted Immuno-PET for Tumor Imaging and Theranostic Approaches.

Monoclonal antibody (mAb)-based therapies have experienced considerable growth in cancer management. When labeled with radionuclides, mAbs also represent promising probes for imaging or theranostic approaches. Initially, mAbs have been radiolabeled with single-photon emitters, such as 131I, 99mTc, or 111In, for diagnostic purposes or to improve radioimmunotherapy (RIT) using dosimetry estimations. Today, more accurate imaging is achieved using positron- emission tomography (PET). Thanks to the important technical advances in the production of PET emitters and their related radiolabeling methods, the last decade has witnessed the development of a broad range of new probes for specific PET imaging. Immuno-PET, which combines the high sensitivity and resolution of a PET camera with the specificity of a monoclonal antibody, is fully in line with this approach. As RIT, immuno-PET can be performed using directly radiolabeled mAbs or using pretargeting to improve imaging contrast. Pretargeted immuno-PET has been developed against different antigens, and promising results have been reported in tumor expressing carcinoembryonic antigen (CEA; CEACAM5) using a bispecific mAb (BsmAb) and a radiolabeled peptide. Medullary thyroid carcinoma (MTC) is an uncommon thyroid cancer subtype which accounts for <10% of all thyroid neoplasms. Characterized by an intense expression of CEA, MTC represents a relevant tumor model for immuno-PET. High sensitivity of pretargeted immunoscintigraphy using murine or chimeric anti-CEA BsMAb and pretargeted haptens-peptides labeled with 111In or 131I were reported in metastatic MTC patients 20 years ago. Recently, an innovative clinical study reported high tumor uptake and contrast using pretargeted anti-CEA immuno-PET in relapsed MTC patients. This review focuses on MTC as an example, but the same pretargeting technique has been applied with success for clinical PET imaging of other CEA-expressing tumors and other pretargeting systems. In particular, those exploiting bioorthogonal chemistry also appear interesting in preclinical animal models, suggesting the high potential of pretargeting for diagnostic and theranostic applications.

Is the sky the limit?

We discuss the use of measurements of the solar granulation contrast as a measure of optical quality. We demonstrate that for data recorded with a telescope that uses adaptive optics and/or post-processing to compensate for many low- and high-order aberrations, the RMS granulation contrast is directly proportional to the Strehl ratio calculated from the residual (small-scale) wavefront error (static and/or from seeing). We demonstrate that the wings of the high-order compensated point spread function for the Swedish 1-m Solar Telescope (SST) are likely to extend to a radius of not more than about 2″, which is consistent with earlier conclusions drawn from stray-light compensation of sunspot images. We report on simultaneous measurements of seeing and solar granulation contrast averaged over 2 s time intervals at several wavelengths from 525 nm to 853.6 nm on the red-beam (CRISP beam) and wavelengths from 395 nm to 484 nm on the blue-beam (CHROMIS beam). These data were recorded with the SST, which has been revamped with an 85-electrode adaptive mirror and a new tip-tilt mirror, both of which were polished to exceptionally high optical quality. Compared to similar data obtained with the previous 37-electrode adaptive mirror in 2009 and 2011, there is a significant improvement in image contrast. The highest 2 s average image contrasts measured in April 2015 through 0.3−0.9 nm interference filters at 525 nm, 557 nm, 630 nm, and 853.5 nm with compensation only for the diffraction limited point spread function of SST are 11.8%, 11.8%, 10.2%, and 7.2%, respectively. Similarly, the highest 2 s contrasts measured at 395 nm, 400 nm, and 484 nm in May 2016 through 0.37−1.3 nm filters are 16%, 16%, and 12.5%, respectively. The granulation contrast observed with SST compares favorably to measured values with SOT on Hinode and with Sunrise as well as major ground-based solar telescopes. Simultaneously with the above wideband red-beam data, we also recorded narrowband continuum images with the CRISP imaging spectropolarimeter. We find that contrasts measured with CRISP are entirely consistent with the corresponding wideband contrasts, demonstrating that any additional image degradation by the CRISP etalons and telecentric optical system is marginal or even insignificant. Finally, we discuss the origin of the 48 nm RMS wavefront error needed to bring consistency between the measured granulation contrast and that obtained from 3D simulations of convection.