Correcting B0 inhomogeneity-induced distortions in whole-body diffusion MRI of bone

Diffusion-weighted magnetic resonance imaging (DWI) of the musculoskeletal system has various applications, including visualization of bone tumors. However, DWI acquired with echo-planar imaging is susceptible to distortions due to static magnetic field inhomogeneities. This study aimed to estimate spatial displacements of bone and to examine whether distortion corrected DWI images more accurately reflect underlying anatomy. Whole-body MRI data from 127 prostate cancer patients were analyzed. The reverse polarity gradient (RPG) technique was applied to DWI data to estimate voxel-level distortions and to produce a distortion corrected DWI dataset. First, an anatomic landmark analysis was conducted, in which corresponding vertebral landmarks on DWI and anatomic T2-weighted images were annotated. Changes in distance between DWI- and T2-defined landmarks (i.e., changes in error) after distortion correction were calculated. In secondary analyses, distortion estimates from RPG were used to assess spatial displacements of bone metastases. Lastly, changes in mutual information between DWI and T2-weighted images of bone metastases after distortion correction were calculated. Distortion correction reduced anatomic error of vertebral DWI up to 29 mm. Error reductions were consistent across subjects (Wilcoxon signed-rank p < 10–20). On average (± SD), participants’ largest error reduction was 11.8 mm (± 3.6). Mean (95% CI) displacement of bone lesions was 6.0 mm (95% CI 5.0–7.2); maximum displacement was 17.1 mm. Corrected diffusion images were more similar to structural MRI, as evidenced by consistent increases in mutual information (Wilcoxon signed-rank p < 10–12). These findings support the use of distortion correction techniques to improve localization of bone on DWI.

Correlative imaging of ferroelectric domain walls

The wealth of properties in functional materials at the nanoscale has attracted tremendous interest over the last decades, spurring the development of ever more precise and ingenious characterization techniques. In ferroelectrics, for instance, scanning probe microscopy based techniques have been used in conjunction with advanced optical methods to probe the structure and properties of nanoscale domain walls, revealing complex behaviours such as chirality, electronic conduction or localised modulation of mechanical response. However, due to the different nature of the characterization methods, only limited and indirect correlation has been achieved between them, even when the same spatial areas were probed. Here, we propose a fast and unbiased analysis method for heterogeneous spatial data sets, enabling quantitative correlative multi-technique studies of functional materials. The method, based on a combination of data stacking, distortion correction, and machine learning, enables a precise mesoscale analysis. When applied to a data set containing scanning probe microscopy piezoresponse and second harmonic generation polarimetry measurements, our workflow reveals behaviours that could not be seen by usual manual analysis, and the origin of which is only explainable by using the quantitative correlation between the two data sets.

Distortion correction for wide angle holographic projector

This letter presents distortion correction method enabling distortion minimized, large size image in wide angle holographic projector. The technique applies numerical predistortion of an input image used for hologram generation. It is based on estimation of distortion coefficients by comparing optically reconstructed point test chart with the original one. Obtained experimental results prove that the technique allows reconstruction of high-quality image. Full Text: PDF ReferencesM. Makowski, Experimental Aspects of Holographic Projection with a Liquid-Crystal-on-Silicon Spatial Light Modulator, in Holographic Materials and Optical Systems, M. Kumar, ed. (IntechOpen, 2019). CrossRef H. Pang, A. Cao, W. Liu, L. Shi, and Q. Deng, "Effective method for further magnifying the image in holographic projection under divergent light illumination", Appl. Opt. 58, 8713 (2019). CrossRef Y. Qi, C. Chang, and J. Xia, "Speckleless holographic display by complex modulation based on double-phase method", Opt. Express 24, 30368 (2016). CrossRef E. Buckley, "Holographic Laser Projection", J. Display Technol. 99, 1 (2010). DirectLink M. Chlipała, T. Kozacki, H. Yeom, J. Martinez-Carranza, R. Kukołowicz, J. Kim, J. Yang, J. Choi, J. Pi, and C. Hwang, "Wide angle holographic video projection display", Opt. Lett. 46, 4956 (2021). CrossRef Z. He, X. Sui, L. Cao and G. Jin, "Image-Distortion Correction Algorithm for Computer-Generated Holographic Display," 2018 IEEE 27th International Symposium on Industrial Electronics (ISIE), 1331 (2018). CrossRef A. Kaczorowski, G.S. Gordon, A. Palani, S. Czerniawski and T.D. Wilkinson, "Optimization-Based Adaptive Optical Correction for Holographic Projectors", J. Display Technol. 11(7), 596 (2015). CrossRef Z. He, X. Sui, G. Jin, L. Cao, "Distortion-Correction Method Based on Angular Spectrum Algorithm for Holographic Display", IEEE Trans. Industr. Inform. 15, 6162 (2019). CrossRef O. Mendoza-Yero, G. Mínguez-Vega, and J. Lancis, "Encoding complex fields by using a phase-only optical element", Opt. Lett. 39, 1740 (2014). CrossRef T. Kozacki, K. Falaggis, "Angular spectrum method with compact space–bandwidth: generalization and full-field accuracy", Appl. Opt. 55, 5014 (2016). CrossRef

Simultaneous Super-Resolution and Distortion Correction for Single-shot EPI DWI using Deep Learning

Single-shot echo planer imaging (SS-EPI) is widely used for clinical Diffusion-weighted magnetic resonance imaging (DWI) acquisitions. However, due to the limited bandwidth along the phase encoding direction, the obtained images suffer from distortion and blurring, which limits its clinical value for diagnosis. Here we proposed a deep learning-based image-quality-transfer method with a novel loss function with improved network structure to simultaneously increase the resolution and correct distortions for SS-EPI. We proposed a modified network structure based on Generative Adversarial Networks (GAN). A dense net with gradient map guidance and a multi-level fusion block was employed as the generator to suppress the over-smoothing effect. We also proposed a fractional anisotropy (FA) loss to exploit the intrinsic signal relations in DWI. In-vivo brain DWI data were used to test the proposed method. The results showed that the distortion-corrected high-resolution DWI images with restored anatomical details can be obtained from low-resolution SS-EPI images by taking the advantage of high-resolution anatomical images. Additionally, the proposed FA loss can improve the image quality and quantitative accuracy of diffusion metrics by utilizing the intrinsic relations among different diffusion directions.

Phantom assessment of three-dimensional geometric distortion of a dedicated wide-bore MR-simulator for radiotherapy

This study evaluated the machine-dependent three-dimensional geometric distortion images acquired from a 1.5T 700mm-wide bore MR-simulator based on a large geometric accuracy phantom. With the consideration of radiation therapy (RT) application requirements, every sequence was examined in various combinations of acquisition-orientations and receiver-bandwidths with console-integrated distortion correction enabled. Distortion was repeatedly measured over a six-month period. The distortion measured from the images acquired at the beginning of this period was employed to retrospectively correct the distortion in the subsequent acquisitions. Geometric distortion was analyzed within the largest field-of-view allowed. Six sequences were examined for comprehensive distortion analysis – VIBE, SPACE, TSE, FLASH, BLADE and PETRA. Based on optimal acquisition parameters, their diameter-sphere-volumes (DSVs) of CT-comparable geometric fidelity (where 1mm distortion was allowed) were 333.6mm, 315.1mm, 316.0mm, 318.9mm, 306.2mm and 314.5mm respectively. This was a significant increase from 254.0mm, 245.5mm, 228.9mm, 256.6mm, 230.8mm and 254.2mm DSVs respectively, when images were acquired using un-optimized parameters. The longitudinal stability of geometric distortion and the efficacy of retrospective correction of console-corrected images, based on prior distortion measurements, were inspected using VIBE and SPACE. The retrospectively corrected images achieved over 500mm DSVs with 1mm distortion allowed. The median distortion was below 1mm after retrospective correction, proving that obtaining prior distortion map for subsequent retrospective distortion correction is beneficial. The systematic evaluation of distortion using various combinations of sequence-type, acquisition-orientation and receiver-bandwidth in a six-month time span would be a valuable guideline for optimizing sequence for various RT applications.

Increased Brain Volumetric Measurement Precision from Multi-Site 3D T1-weighted 3T Magnetic Resonance Imaging by Correcting Geometric Distortions

Magnetic resonance imaging (MRI) scanner-specific geometric distortions may contribute to scanner induced variability and decrease volumetric measurement precision for multi-site studies. The purpose of this study was to determine whether geometric distortion correction increases the precision of brain volumetric measurements in a multi-site multi-scanner study. Geometric distortion variation was quantified over a one-year period at 10 sites using the distortion fields estimated from monthly 3D T1-weighted MRI geometrical phantom scans. The variability of volume and distance measurements were quantified using synthetic volumes and a standard quantitative MRI (qMRI) phantom. The effects of geometric distortion corrections on MRI derived volumetric measurements of the human brain were assessed in two subjects scanned on each of the 10 MRI scanners and in 150 subjects with cerebrovascaular disease (CVD) acquired across imaging sites. Geometric distortions were found to vary substantially between different MRI scanners but were relatively stable on each scanner over a one-year interval. Geometric distortions varied spatially, increasing in severity with distance from the magnet isocenter. In measurements made with the qMRI phantom, the geometric distortion correction decreased the standard deviation of volumetric assessments by 35% and distance measurements by 42%. The average coefficient of variance decreased by 16% in gray matter and white matter volume estimates in the two subjects scanned on the 10 MRI scanners. Geometric distortion correction using an up-to-date correction field is recommended to increase precision in volumetric measurements made from MRI images.