Geometric Distortion Research Articles

44.1: Invited Paper: The Effect Investigation and Objective Quantification of Dynamic Spatial Distortions on VIMS

The mismatches among 3D content acquisition, display, and perception configurations can result in geometric distortion, which is a potential factor affecting the symptom of VIMS. 3D videos simulating two mismatch types and the reference matched situation were customized for the perception experiment. The subjective SSQ, five‐scale VIMS level rating and objective postural instability are adopted as the evaluation metrics. The results show that the factor matched type represented spatial distortion has a significant effect on the subjective VIMS level and objective postural instability metrics (p<0.05). The VIMS level and postural instability increments of the match type are significantly lower than that of mismatch types. Besides, indexes based on Elastic Potential Energy are proposed for the objective quantification of dynamic spatial distortions.

MP52-01 ADOPTING MACHINE VISION AUGMENTATION TO DETECT DETRUSOR INSTABILITY IN OVERACTIVE BLADDER: A FRONTIER OF ARTIFICIAL INTELLIGENCE APPLICATION IN FUNCTIONAL UROLOGY

You have accessJournal of UrologyCME1 Apr 2023MP52-01 ADOPTING MACHINE VISION AUGMENTATION TO DETECT DETRUSOR INSTABILITY IN OVERACTIVE BLADDER: A FRONTIER OF ARTIFICIAL INTELLIGENCE APPLICATION IN FUNCTIONAL UROLOGY Yu Guang Tan, Shauna Woo, Jin Yong, and Lay Guat Ng Yu Guang TanYu Guang Tan More articles by this author , Shauna WooShauna Woo More articles by this author , Jin YongJin Yong More articles by this author , and Lay Guat NgLay Guat Ng More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003300.01AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Overactive bladder (OAB) is an increasingly prevalent urological condition. Routine urodynamics study (UDS) is invasive, inconsistent and simply impractical in every outpatient setting. We propose a novel machine vision augmentative model on cystoscopic images to identify segments of detrusor overactivity (DO) based on motion differences of the vascular network across time. METHODS: We prospectively collected 158 cystoscopy videos [38 previously UDS confirmed DO, 120 non-OAB] and extracted 30 seconds clip from each video, with an image capture rate of 24 frames/sec, amounting to >100,000 frames. The recordings were first denoised to remove artefacts and account for the cystoscopic movements, and have the resolutions enhanced with a set of Deep Learning techniques. Following which, the vascular network is segmented out and multiple key points are determined along the visualised blood vessels. An average of ∼300 key points were identified on each frame captured. Next, mosaic stitching is performed to reconstruct the extracted 2D images into a 3D bladder map to account for the geometric distortions. Finally, the motion differences of the key points across timeframes are tracked as a surrogate for areas of detrusor microcontraction. RESULTS: The structure-from-motion pipeline demonstrated satisfactory 3D reconstructions of the processed cystoscopy videos. The AI-based semantic image segmentation was trained to differentiate UDS confirmed DO from non-OAB patients with a coefficient score of 0.613. The motion differences could be tracked both quantitatively (number of key points) and qualitatively (extent of displacement of key points over time). Areas of exaggerated motion differences detected would represent increased focal detrusor contractions. CONCLUSIONS: This novel machine vision augmentation model yields promising results in identifying OAB patients based on cystoscopy. Potential identification of detrusor microcontraction points can aid targeted drug delivery to enhance treatment efficacy. Source of Funding: Not applicable © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e702 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Yu Guang Tan More articles by this author Shauna Woo More articles by this author Jin Yong More articles by this author Lay Guat Ng More articles by this author Expand All Advertisement PDF downloadLoading ...

Algorithm for Correction of Geometric Distortions of Hyperspectral Images Formed during Angular Oscillations of an Unmanned Aerial Vehicle

Algorithm for Correction of Geometric Distortions of Hyperspectral Images Formed during Angular Oscillations of an Unmanned Aerial Vehicle

The concept of aerial photography using a two-element active optoelectronic complex

The article proposes the concept of obtaining images on the basis of which it is possible to create three-dimensional models of objects. In particular, images contain the data necessary to recreate the three-dimensional form of an object. Such data include: the length, width of the modeled object as well as the lengthening of the shadow cast on the base surface. In accordance with the proposed concept, an important condition for obtaining images suitable for interpretation is the use of spatially separated equipment generating and recording optical radiation. The orientation parameters of the illumination source and the camera are selected, taking into account the requirements for the photogrammetric quality of images. A characteristic of geometric distortions that occur when changing the shooting mode from plan to perspective is presented, which demonstrates the change in the aspect ratio of the image depending on the angle of the camera. A characteristic of the shadow elongation depending on the spatial position of the optical radiation source is presented, which shows the influence of the orientation parameters of the optical illumination means on the length of the shadow cast on the base surface. On the basis of these characteristics, the choice of parameters of relative orientation in space of the source of optical illumination and the equipment that detects optical radiation is substantiated. Predicting the value of geometric distortions of images at the stage of choosing the parameters of relative orientation of the equipment of a two-element active optoelectronic complex allows you to save the photogrammetric quality of images and, as a result, measure the length and width of an object. Predicting the magnitude of the shadow elongation under conditions of artificial optical illumination provides the possibility of transferring features in the image for calculating the applicate and, as a result, recreating the three-dimensional shape of the object. The proposed concept of image registration finds application in topographic and geodetic and engineering work in conditions of insufficient natural light. For example, the use of a two-element active optical-electronic complex makes it possible to obtain three-dimensional photo plans of the terrain of geographic regions with a short daylight hours.

Two-Way Generation of High-Resolution EO and SAR Images via Dual Distortion-Adaptive GANs

Synthetic aperture radar (SAR) provides an all-weather and all-time imaging platform, which is more reliable than electro-optical (EO) remote sensing imagery under extreme weather/lighting conditions. While many large-scale EO-based remote sensing datasets have been released for computer vision tasks, there are few publicly available SAR image datasets due to the high costs associated with acquisition and labeling. Recent works have applied deep learning methods for image translation between SAR and EO. However, the effectiveness of those techniques on high-resolution images has been hindered by a common limitation. Non-linear geometric distortions, induced by different imaging principles of optical and radar sensors, have caused insufficient pixel-wise correspondence between an EO-SAR patch pair. Such a phenomenon is not prominent in low-resolution EO-SAR datasets, e.g., SEN1-2, one of the most frequently used datasets, and thus has been seldom discussed. To address this issue, a new dataset SN6-SAROPT with sub-meter resolution is introduced, and a novel image translation algorithm designed to tackle geometric distortions adaptively is proposed in this paper. Extensive experiments have been conducted to evaluate the proposed algorithm, and the results have validated its superiority over other methods for both SAR to EO (S2E) and EO to SAR (E2S) tasks, especially for urban areas in high-resolution images.

Towards a robust and portable pipeline for quad meshing: Topological initialization of injective integer grid maps

Integer Grid Maps (IGMs) are a class of mappings characterized by integer isolines that align up to unit translations and rotations of multiples of 90 degrees. They are widely used in the context of remeshing, to lay a quadrilateral grid onto the mapped surface. The presence of both discrete and continuous degrees of freedom makes the computation of IGMs extremely challenging. In particular, solving for all degrees of freedom altogether leads to a mixed-integer problem that is known to be NP-Hard. Such a problem can only be solved heuristically, occasionally failing to produce a valid quadrilateral mesh. In this paper we propose a simple topological construction that allows to reduce the problem of computing a valid IGM to the one of mapping a topological disk to a convex domain. This is a much easier problem to deal with, because it completely removes the integer constraints, permitting to obtain a provably injective parameterization that is guaranteed to incorporate all the correct integer transitions with a simple linear solve. Not only the proposed algorithm is easy to implement, but it is also independent from costly numerical solvers that are unavoidable in existing quadmeshing pipelines, preventing their exploitation in open source or low-budget projects. Despite provably correct, the so generated maps contain a considerable amount of geometric distortion and a poor quad connectivity, making this technique more suitable for a robust initialization rather than for the computation of an application-ready IGM. In the article we present the details of our construction, also analyzing its geometric and topological properties.

Thermomechanical Process Simulation and Experimental Verification for Laser Additive Manufacturing of Inconel®718

Laser cladding has emerged as a promising technique for custom-built fabrications, remanufacturing, and repair of metallic components. However, frequent melting and solidification in the process cause inevitable residual stresses that often lead to geometric discrepancies and deterioration of the end product. The accurate physical interpretation of the powder consolidation process remains challenging. Thermomechanical process simulation has the potential to comprehend the layer-by-layer additive process and subsequent part-scale implications. Nevertheless, computational accuracy and efficacy have been serious concerns so far; therefore, a hybrid FEM scheme is adopted for efficient prediction of the temperature field, residual stress, and distortion in multilayer powder-fed laser cladding of Inconel®718. A transient material deposition with powder material modeling is schematized to replicate the fabrication process. Moreover, simulation results for residual stress and distortion are verified with in-house experiments, where residual stress is measured with XRD (X-Ray Diffraction) and geometric distortion is evaluated with CMM (Coordinate Measuring Machine). A maximum tensile residual stress of 373 ± 5 MPa is found in the vicinity of the layer right in the middle of the substrate and predicted results are precisely validated with experiments. Similarly, a 0.68 ± 0.01 mm distortion is observed with numerical simulation and showed a precise agreement with experimental data for the same geometry and processing conditions. Conclusively, the implemented hybrid FEM approach demonstrated a robust and accurate prediction of transient temperature field, residual stresses, and geometric distortion in the multilayer laser cladding of Inconel®718.

A blind watermarking algorithm based on specific component quantization in DHT domain

For meeting the higher demands of color image ownership protection in the fifth-generation (5 G) communication network, a blind watermarking algorithm based on specific component quantization of discrete Hartley transform (DHT) is proposed. At first, the color cover image is partitioned into the non-overlapping blocks of sized 4 × 4, and the DHT component of the selected block at specific location is calculated; then the inherent correlation in RGB channels and quantization index modulation (QIM) technique are used to obtain the component difference; finally, without global DHT of forward and inverse, the color watermark logo is inserted into the cover image by the derived modification method. Moreover, RSA public-key encryption algorithm is applied to scramble the parameters of Affine transform, which guarantees the double-layer security of watermark itself and algorithm secret keys. When extracting watermark, an image correction strategy based on geometric features is realized to resist geometric distortion. Experiment results show that the proposed algorithm has low computational complexity, strong robustness and high security at the foundation of good invisibility and large payload, which overcomes the shortcoming of slow execution speed of transform-domain watermarking and has high feasibility of fast copyright protection in 5 G environment.

Improved astrometric calibration of Cassini narrow angle camera images and its accurate geometric distortion model

天体测量定标是高精度位置测量的基础。空间望远镜图像的天体测量定标是我国计划于2024年发射空间站望远镜需要突破的关键技术。本文以“卡西尼” (Cassini)飞行器窄视场照相机 (Narrow Angle Camera，NAC)拍摄的图像为例，探究了CCD图像天体测量定标技术，希望为拓展应用到我国即将发射的空间站望远镜提供有益的参考。具体地，本文选取了NAC在五个历元 (2006，2008，2010，2014，2016)拍摄的具有不同指向和取向观测密集星场的图像，探究了空间图像高精度天体测量的归算方法，求解出了各历元的CCD扭曲模型。相比目前其他学者的归算结果，本文在恒星的位置测量精度上有较大的提高。对于在2.6秒曝光时间11~12星等 (Gaia-G星等)的恒星，平均(O-C) (The Observed Minus Computed)的标准差在x和y坐标方向分别为约0.04像素 (约提高0.5倍)和0.03像素 (约提高1倍)。通过分析各历元图像的扭曲模型，本文发现在飞行器执行任务期间CCD图像的扭曲保持了良好的稳定性。在1024×1024像素尺度下，几何扭曲的最大值、中值、最小值分别为0.184 ± 0.023，0.038 ± 0.005和0.007 ± 0.003像素。根据求解扭曲的平均模型，本文提供了模型的数值表达式及改正方法。

Energy balances for the collision of gravity currents of equal strengths

Collision of two counterflowing gravity currents of equal densities and heights was investigated by means of three-dimensional high-resolution simulations with the goal of understanding the flow structures and energetics in the collision region in more detail. The lifetime of collision is approximately $3 \tilde {H}/\tilde {u}_f$ , where $\tilde {H}$ is the depth of heavy and ambient fluids, and $\tilde {u}_f$ is the front velocity of the approaching gravity currents, and the lifetime of collision can be divided into three phases. During Phase I, $-0.2 \leqslant (\tilde {t}-\tilde {t}_c) \tilde {u}_f/\tilde {H} \leqslant 0.5$ , where $\tilde {t}$ is the time, and $\tilde {t}_c$ is the time instance at which the two colliding gravity currents have fully osculated, geometric distortions of the gravity current fronts result in stretching of pre-existing vorticity in the wall-normal direction inside the fronts, and an array of vertical vortices extending throughout the updraught fluid column develop along the interface separating the two colliding gravity currents. The array of vertical vortices is responsible for the mixing between the heavy fluids of the two colliding gravity currents and for the production of turbulent kinetic energy in the collision region. The presence of the top boundary deflects the updraughts into the horizontal direction, and a number of horizontal streamwise vortices are generated close to the top boundary. During Phase II, $0.5 \leqslant (\tilde {t}-\tilde {t}_c) \tilde {u}_f/\tilde {H} \leqslant 1.2$ , the horizontal streamwise vortices close to the top boundary induce turbulent buoyancy flux and break up into smaller structures. While the production of turbulent kinetic energy weakens, the rate of transfer of energy to turbulent flow due to turbulent buoyancy flux reaches its maximum and becomes the primary supply in the turbulent kinetic energy in Phase II. During Phase III, $1.2 \leqslant (\tilde {t}-\tilde {t}_c) \tilde {u}_f/\tilde {H} \leqslant 2.8$ , the collided fluid slumps away from the collision region, while the production of turbulent kinetic energy, turbulent buoyancy flux and dissipation of energy attenuate. From the point of view of energetics, the production of turbulent kinetic energy and turbulent buoyancy flux transfers energy away from the mean flow to the turbulent flow during the collision. Our study complements previous experimental investigations on the collision of gravity currents in that the flow structures, spatial distribution and temporal evolution of the mean flow and turbulent flow characteristics in the collision region are presented clearly. It is our understanding that such complete information on the energy budgets in the collision region can be difficult to attain in laboratory experiments.

Automated geometric precise correction of medium remote sensing images based on ASTER global digital elevation model

Accurate and unified information from the increasingly remote sensing (RS) scenes is important for RS applications in multi-sectoral association services of natural resource management. However, these applications in mountain areas are limited by the challenging issues of random geometric distortions and erroneous spatial associations. The paper introduces digital elevation model (DEM) maps as a unified geographic reference to search and match homonymy ground points (HGPs). The proposed computer-based procedure was tested with Landsat TM, ETM and HJ-1B satellite images using ASTER global DEM in the Longitudinal Rang-gorge Valley Region of Southwest China. 1322, 3551 and 694 pairs of HGPs were identified and acquired the geometric accuracies with 43 m (TM), 14 m (ETM) and 123 m (HJ), respectively. The deviations are significantly reduced and the disjoint ground objects are matched. The study satisfies the application requirement of multispectral satellite imagery with less labour and time costs.

A Semantic Cognition Contribution to Mood and Anxiety Disorder Pathophysiology.

Over the last two decades, the functional role of the bilateral anterior temporal lobes (bATLs) has been receiving more attention. They have been associated with semantics and social concept processing, and are regarded as a core region for depression. In the past, the role of the ATL has often been overlooked in semantic models based on functional magnetic resonance imaging (fMRI) due to geometric distortions in the BOLD signal. However, previous work has unequivocally associated the bATLs with these higher-order cognitive functions following advances in neuroimaging techniques to overcome the geometric distortions. At the same time, the importance of the neural basis of conceptual knowledge in understanding mood disorders became apparent. Theoretical models of the neural basis of mood and anxiety disorders have been classically studied from the emotion perspective, without concentrating on conceptual processing. However, recent work suggests that the ATL, a brain region underlying conceptual knowledge, plays an essential role in mood and anxiety disorders. Patients with anxiety and depression often cope with self-blaming biases and guilt. The theory is that in order to experience guilt, the brain needs to access the related conceptual information via the ATL. This narrative review describes how aberrant interactions of the ATL with the fronto-limbic emotional system could underlie mood and anxiety disorders.

Glass façade segmentation and repair for aerial photogrammetric 3D building models with multiple constraints

Aerial photogrammetric three-dimensional (3D) city models provide photorealistic virtual scenes for various applications, such as urban planning, autonomous driving, emergency management, etc. With the rapid progress of urbanization, glass façades commonly exist on buildings, which cannot be well reconstructed with geometric deformation and distortion due to the limitation of the image-based Multi-View Stereo (MVS) modeling pipeline. The distorted glass façades make building models visually unreal and messy. This paper proposes a workflow to segment and repair glass façades in aerial photogrammetric 3D building models with multiple constraints to resolve the problem, mainly including two aspects: 1) projection-based glass façade segmentation with geometric information and multi-view constraints, and 2) glass façade model repair via mesh smoothing and texture mapping. First, an efficient approach for façade information extraction is proposed, which utilizes the density of the reprojected point clouds and elevation differences because the typical structure of building façades is usually vertically aligned to the ground surface. Second, we project the façade mesh onto the multi-view oblique aerial images. The glass façades are predicted by a deep learning-based semantic segmentation method to distinguish the glass façades. Finally, based on the extracted glass façades, we remedy the geometric deformation using a mesh denoising method by grouping strategy with edge constraints. After smoothing the mesh structure of glass façades, we remap the texture to generate the completed 3D models with optimized glass façades. Our method leverages multiple constraints, including multi-view constraints, façade structure constraints, grouping strategy, and boundary constraints. The multi-view and façade structure constraints help decrease the adverse effects caused by false segmentation; the grouping strategy and boundary constraints can avoid disorders in some specific areas and preserve the sharp feature in the adjacent regions. Thus, our approach is robust and does not worsen the 3D model. Experiments demonstrate that our workflow is feasible for glass façade segmentation and repair for aerial photogrammetric 3D building models.

Landslide Detection Using Time-Series InSAR Method along the Kangding-Batang Section of Shanghai-Nyalam Road

Due to various factors such as urban development, climate change, and tectonic movements, landslides are a common geological phenomenon in the Qinghai–Tibet Plateau region, especially on both sides of a road, where large landslide hazards often result in traffic disruptions and casualties. Identifying the spatial distribution of landslides and monitoring their stability are essential for predicting landslide occurrence and implementing prevention measures. In this study, taking the Kangding-Batang section of Shanghai-Nyalam Road as the study area, we adopted a semi-automated time-series interferometric synthetic aperture radar (InSAR) method to identify landslides and monitor their activity. A total of 446 Sentinel-1 ascending and descending SAR images from January 2018 to December 2021 were thus collected and processed by using open-source InSAR processing software. After a series of error corrections, we obtained surface deformation maps covering the study area, and a total of 236 potential landslides were subsequently identified and classified into three categories, namely slow-sliding rockslides, debris flows, and debris avalanches, by combining deformation maps, optical images, and a digital elevation model (DEM). For a typical landslide, we performed deformation decomposition and analyzed the relationship between its deformation and rainfall, revealing the contribution of rainfall to the landslide. In addition, we discussed the effect of SAR geometric distortion on landslide detection, highlighting the importance of joint ascending and descending observations in mountainous areas. We analyzed the controlling factors of landslide distribution and found that topographic conditions are still the dominant factor. Our results may be beneficial for road maintenance and disaster mitigation. Moreover, the entire processing is semi-automated based on open-source tools or software, which provides a paradigm for landslide-related studies in other mountainous regions of the world.

SIFNet: A self-attention interaction fusion network for multisource satellite imagery template matching

Multisource satellite images provide abundant and complementary earth observations, while nonlinear radiometric and geometric distortions (such as scale and rotation variations) between these multimodal images pose remarkable challenges for further remote sensing applications, such as change detection. We therefore proposed a template matching algorithm based on self-attention interactive fusion network, named SIFNet, to align multisource satellite images. First, a feature pyramid network was first conducted to extract multiscale features for each pixel, with the template and reference images as the inputs. Then, the extracted features were fused by self-attention layers in Transformer for information interaction. Third, the similarity and semantic matching loss functions were developed to convert satellite imagery registration into regression task, allowing SIFNet aligning multimodal patch images more efficiently based on point-to-point correspondence, instead of globally searching extremums as previous matching strategies did. We performed experiments based on four multimodal datasets (i.e. Google, GF-2, Landsat-8 and optical-SAR images) with various scenes to evaluate the performance and robustness of SIFNet. The results demonstrate the proposed SIFNet performed a comparable accuracy for template matching with other algorithms and was robust to geometric distortions and radiometric variations of multisource remote sensing data.

Cover Picture: Astron. Nachr. 03/2023

Vector plots of the Geometric distortion (GD) solution for the James Webb Telescope NIRCam long wavelength channel detectors #5 of both module A (left) and module B (right), showing the size of the residual vectors, magnified by a factor of 20. The color map represents the pixels' area variation across the detectors due to the GD correction. Details are presented in the article by M. Griggio et al. (this issue of AN, e230006) where the authors describe their correction procedure and its validation. Along with their geometric-distortion solution, they make available their Python software to convert the raw-pixels coordinates of each detector into distortion-free positions, and to put all ten detectors of NIRCam into a common reference system.

Early Identification and Influencing Factors Analysis of Active Landslides in Mountainous Areas of Southwest China Using SBAS−InSAR

Potential landslides in the mountainous areas of southwest China pose a serious threat to the lives and property of local residents. Synthetic aperture radar interferometry (InSAR) technology has the advantages of wide coverage, all weather applicability, and low cost and can quickly and accurately identify large range of active landslides, making it a useful geodetic tool for the early identification and prevention of landslides. This paper employed small baseline subset InSAR (SBAS−InSAR) technology and ascending and descending Sentinel−1 data from January 2019 to December 2021 to early identify active landslides in the Maoxian County to Li County National Highway (G317 and G213). The InSAR deformation results were verified by geometric distortion analysis, optical remote sensing interpretation, and field investigation, and 115 active landslides were successfully determined, among which 23 active landslides were identified by ascending and descending Sentinel−1 data together. In addition, InSAR deformation results show that fault, stratigraphic lithology, and rainfall are the three main factors that accelerate the deformation of active landslides and can trigger new active landslides. This study can provide an important reference for the early identification and prevention of landslides in mountainous areas.

Self-Referenced Method for Geometrical Distortion Removal in THz Time-Domain Reflection Imaging

In this article, we develop a method for removing the phase drift induced by physically distorted object in terahertz time-domain reflection imaging (THz-TDRI). The proposed approach is defined as self-referenced, as it does not rely on any numerical parameter optimization nor extra instrumental components, and it is based on the unique manipulation of time-domain imaging data. In fact, we demonstrate that the problem can be solved assuming a linear contribution of the temporal shift induced by surface curvature. We illustrate how the self-referenced method is modeled and implemented, and we report the results obtained on two objects with different characteristics: a tilted and highly reflective surface, and a warped and heterogeneous surface. The proposed method demonstrates how to successfully remove the phase alterations induced on the reflected electric field, and how to repair the heavily corrupted images in the frequency-domain.

Virtual Sensor-Based Geometry Prediction of Complex Sheet Metal Parts Formed by Robotic Rollforming

Sheet metal parts can often replace milled components, strongly improving the buy-to-fly ratio in the aeronautical sector. However, the sheet metal forming of complex parts traditionally requires expensive tooling, which is usually prohibitive for low manufacturing rates. To achieve precise parts, non-productive and cost-intensive geometry straightening processes are additionally often required after forming. Rollforming is a possible technology for producing profiles at large rates. For low manufacturing rates, robotic rollforming can be an interesting option, significantly reducing investment at the cost of higher manufacturing times while keeping a high process flexibility. Forming is performed incrementally by a single roller set moved by the robot along predefined bending curves. The present work’s contribution to the overall solution is the development of an intelligent algorithm to calculate geometry after a robotic rollforming process based on process reaction forces. This information is required for in-process geometric distortion correction. Reaction forces and torques are acquired during the process, and geometry is calculated based on artificial intelligence (AI) applied to that information. The present paper describes the AI development for this virtual geometry sensing system.

Intraobserver and Interobserver Reproducibility of Breast Diffusion-Weighted Imaging Quantitative Parameters: Readout-Segmented vs. Single-Shot Echo-Planar Imaging.

The recommended technique for breast diffusion-weighted imaging (DWI) acquisitions is not sufficiently standardized in clinical practice. To investigate the intraobserver and interobserver reproducibility of DWI measurements, diffusion-kurtosis imaging (DKI) parameters, and image quality evaluation in breast lesions between single-shot echo-planar imaging (ss-EPI) and readout-segmented echo-planar imaging (rs-EPI). Prospective. A total of 295 women with 209 malignant and 86 benign breast lesions. A 3-T; fat-saturated T2-weighted MR imaging (T2WI); multi-b-value DWI with both ss-EPI and rs-EPI readouts; T1-weighted dynamic contrast-enhanced MRI (DCE-MRI). Mean kurtosis (MK), mean diffusion (MD), and apparent diffusion coefficient (ADC) values were measured for each lesion on ss-EPI and rs-EPI, respectively. Image quality was visually evaluated regarding image sharpness, geometric distortion, lesion conspicuity, visualization of anatomic structures, and overall quality. Quantitative and qualitative analyses were performed twice with a time interval of 2 weeks. Intraobserver and interobserver reproducibility wereevaluated using intra-class correlation coefficients (ICC), within-subject coefficient of variation (wCV), and Bland-Altman plots. MK, MD, and ADC quantitative parameters for breast lesions showed excellent intraobserver and interobserver reproducibility, with ICCs >0.75 and wCV values ranging from 2.51% to 7.08% for both sequences. The wCV values in both intraobserver and interobserver measurements were higher in the ss-EPI sequence (3.63%-7.08%) than that of the rs-EPI sequence (2.51%-3.62%). The wCV values differed in subgroups with different histopathological types of lesions, breast density, lesion morphology, and lesion sizes, respectively. Furthermore, rs-EPI (ICCs, 0.76-0.97; wCV values, 2.41%-6.04%) had better intraobserver and interobserver reproducibility than ss-EPI (ICCs, 0.54-0.90; wCV values, 6.18%-13.69%) with regard to image quality. Compared to the ss-EPI, the rs-EPI sequence showed higher intraobserver and interobserver reproducibility for quantitative diffusion-related parameters and image quality assessments measured in breast DWI and DKI. 2. Stage 2.