A metabolite specific 3D stack-of-spirals bSSFP sequence for improved bicarbonate imaging in hyperpolarized [1-13C]Pyruvate MRI

13C-bicarbonate is a crucial measure of pyruvate oxidation and TCA cycle flux, but is challenging to measure due to its relatively low concentration and thus will greatly benefit from improved signal-to-noise ratio (SNR). To address this, we developed and investigated the feasibility of a 3D stack-of-spirals metabolite-specific balanced steady-state free precession (MS-bSSFP) sequence for improving the SNR and spatial resolution of dynamic 13C-bicarbonate imaging in hyperpolarized [1-13C]pyruvate studies. The bicarbonate MS-bSSFP sequence was evaluated by simulations, phantoms studies, preclinical studies on five rats, brain studies on two healthy volunteers and renal study on one renal cell carcinoma patient. The simulations and phantom results showed that the bicarbonate-specific pulse had minimal perturbation of other metabolites (<1%). In the animal studies, the MS-bSSFP sequence provided an approximately 2.6-3 × improvement in 13C-bicarbonate SNR compared to a metabolite-specific gradient echo (MS-GRE) sequence without altering the bicarbonate or pyruvate kinetics, and the shorter spiral readout in the MS-bSSFP approach reduced blurring. Using the SNR ratio between MS-bSSFP and MS-GRE, the T2 values of bicarbonate and lactate in the rat kidneys were estimated as 0.5 s and 1.1 s, respectively. The in-vivo feasibility of bicarbonate MS-bSSFP sequence was demonstrated in two human brain studies and one renal study. These studies demonstrate the potential of the sequence for in-vivo applications, laying the foundation for future studies to observe this relatively low concentration metabolite with high-quality images and improve measurements of pyruvate oxidation

Monte Carlo-based Noise Compensation in Coil Intensity Corrected Endorectal MRI

Background: Prostate cancer is one of the most common forms of cancer found in males making early diagnosis important. Magnetic resonance imaging (MRI) has been useful in visualizing and localizing tumor candidates and with the use of endorectal coils (ERC), the signal-to-noise ratio (SNR) can be improved. The coils introduce intensity inhomogeneities and the surface coil intensity correction built into MRI scanners is used to reduce these inhomogeneities. However, the correction typically performed at the MRI scanner level leads to noise amplification and noise level variations. Methods: In this study, we introduce a new Monte Carlo-based noise compensation approach for coil intensity corrected endorectal MRI which allows for effective noise compensation and preservation of details within the prostate. The approach accounts for the ERC SNR profile via a spatially-adaptive noise model for correcting non-stationary noise variations. Such a method is useful particularly for improving the image quality of coil intensity corrected endorectal MRI data performed at the MRI scanner level and when the original raw data is not available. Results: SNR and contrast-to-noise ratio (CNR) analysis in patient experiments demonstrate an average improvement of 11.7 dB and 11.2 dB respectively over uncorrected endorectal MRI, and provides strong performance when compared to existing approaches. Conclusions: A new noise compensation method was developed for the purpose of improving the quality of coil intensity corrected endorectal MRI data performed at the MRI scanner level. We illustrate that promising noise compensation performance can be achieved for the proposed approach, which is particularly important for processing coil intensity corrected endorectal MRI data performed at the MRI scanner level and when the original raw data is not available.Comment: 23 page

On the effect of image denoising on galaxy shape measurements

Weak gravitational lensing is a very sensitive way of measuring cosmological parameters, including dark energy, and of testing current theories of gravitation. In practice, this requires exquisite measurement of the shapes of billions of galaxies over large areas of the sky, as may be obtained with the EUCLID and WFIRST satellites. For a given survey depth, applying image denoising to the data both improves the accuracy of the shape measurements and increases the number density of galaxies with a measurable shape. We perform simple tests of three different denoising techniques, using synthetic data. We propose a new and simple denoising method, based on wavelet decomposition of the data and a Wiener filtering of the resulting wavelet coefficients. When applied to the GREAT08 challenge dataset, this technique allows us to improve the quality factor of the measurement (Q; GREAT08 definition), by up to a factor of two. We demonstrate that the typical pixel size of the EUCLID optical channel will allow us to use image denoising.Comment: Accepted for publication in A&A. 8 pages, 5 figure

Improving and Assessing Planet Sensitivity of the GPI Exoplanet Survey with a Forward Model Matched Filter

We present a new matched filter algorithm for direct detection of point sources in the immediate vicinity of bright stars. The stellar Point Spread Function (PSF) is first subtracted using a Karhunen-Lo\'eve Image Processing (KLIP) algorithm with Angular and Spectral Differential Imaging (ADI and SDI). The KLIP-induced distortion of the astrophysical signal is included in the matched filter template by computing a forward model of the PSF at every position in the image. To optimize the performance of the algorithm, we conduct extensive planet injection and recovery tests and tune the exoplanet spectra template and KLIP reduction aggressiveness to maximize the Signal-to-Noise Ratio (SNR) of the recovered planets. We show that only two spectral templates are necessary to recover any young Jovian exoplanets with minimal SNR loss. We also developed a complete pipeline for the automated detection of point source candidates, the calculation of Receiver Operating Characteristics (ROC), false positives based contrast curves, and completeness contours. We process in a uniform manner more than 330 datasets from the Gemini Planet Imager Exoplanet Survey (GPIES) and assess GPI typical sensitivity as a function of the star and the hypothetical companion spectral type. This work allows for the first time a comparison of different detection algorithms at a survey scale accounting for both planet completeness and false positive rate. We show that the new forward model matched filter allows the detection of $50\%$ fainter objects than a conventional cross-correlation technique with a Gaussian PSF template for the same false positive rate.Comment: ApJ accepte

Depth Superresolution using Motion Adaptive Regularization

Spatial resolution of depth sensors is often significantly lower compared to that of conventional optical cameras. Recent work has explored the idea of improving the resolution of depth using higher resolution intensity as a side information. In this paper, we demonstrate that further incorporating temporal information in videos can significantly improve the results. In particular, we propose a novel approach that improves depth resolution, exploiting the space-time redundancy in the depth and intensity using motion-adaptive low-rank regularization. Experiments confirm that the proposed approach substantially improves the quality of the estimated high-resolution depth. Our approach can be a first component in systems using vision techniques that rely on high resolution depth information