Geometric Distortion Research Articles

Effects of short-range order on phase equilibria and opto-electronic properties of ternary alloy ZnxCd1-xTe

We employ first principles methods based on density functional theory and beyond to study ZnxCd1-xTe, 0≤x≤1, alloys in the zinc blende (B3) crystal structure. Cluster Expansion and Monte Carlo formalisms were deployed to provide a phase diagram determining consolute temperature of 387 K at 40% Zn concentration. Opto-electronic properties are computed with the hybrid HSE06 functional for disordered ZnxCd1-xTe alloys, which were simulated using special quasi-random structures. Bowing effects in the bandgap and effective carrier masses were observed in alloying which can be attributed to local geometrical distortions as portrayed by bond length distributions. Downward bowing in the electronic bandgap will be beneficial in photovoltaic applications through increased net photocurrent. Absorption coefficients show robust absorption in ZnxCd1-xTe as indicated by substantial optical absorption throughout all Zn concentrations, aided by low reflectivity that ensures a high absorption. Presence of short-range order in Zn0.25Cd0.75Te was observed through clustering and anti-clustering among different cationic species of Zn and Cd. It has a value of 0.11 at 1000 K compared to −0.79 at 400 K. The bandgap of Zn0.25Cd0.75Te at 1000 K was found to be slightly higher, 0.05 eV, than at 400 K, consistent with the value of short-range order. Thus, short-range order and possibly composition can be used in the design and synthesis of the appropriate solar cell, thereby improving the performance in this system.

The TinyV3RSE Hardware-in-the-Loop Vision-Based Navigation Facility

The increase in number of interplanetary probes has emphasized the need for spacecraft autonomy to reduce overall mission costs and to enable riskier operations without ground support. The perception of the external environment is a critical task for autonomous probes, being fundamental for both motion planning and actuation. Perception is often achieved using navigation sensors which provide measurements of the external environment. For space exploration purposes, cameras are among the sensors that provide navigation information with few constraints at the spacecraft system level. Image processing and vision-based navigation algorithms are exploited to extract information about the external environment and the probe's position within it from images. It is thus crucial to have the capability to generate realistic image datasets to design, validate, and test autonomous algorithms. This goal is achieved with high-fidelity rendering engines and with hardware-in-the-loop simulations. This work focuses on the latter by presenting a facility developed and used at the Deep-space Astrodynamics Research and Technology (DART) Laboratory at Politecnico di Milano. First, the facility design relationships are established to select hardware components. The critical design parameters of the camera, lens system, and screen are identified and analytical relationships are developed among these parameters. Second, the performances achievable with the chosen components are analytically and numerically studied in terms of geometrical accuracy and optical distortions. Third, the calibration procedures compensating for hardware misalignment and errors are defined. Their performances are evaluated in a laboratory experiment to display the calibration quality. Finally, the facility applicability is demonstrated by testing imageprocessing algorithms for space exploration scenarios.

Geo-Metric

In this work we take a novel perception-centered approach to quantify distortions on 3D geometry of faces, to which humans are particularly sensitive. We generated a dataset, composed of 100 high-quality and demographically-balanced face scans. We then subjected these meshes to distortions that cover relevant use cases in computer graphics, and conducted a large-scale perceptual study to subjectively evaluate them. Our dataset consists of over 84,000 quality comparisons, making it the largest ever psychophysical dataset for geometric distortions. Finally, we demonstrated how our data can be used for applications like metrics, compression, and level-of-detail rendering.

Experimental Evaluation of Display Field Communication Based on Machine Learning and Modem Design

Display field communication (DFC) is a frequency-domain unobtrusive display-to-camera (D2C) communication, in which an electronic display serves as a transmitter and a camera serves as a receiver. In this paper, we propose a machine learning-based DFC scheme and evaluate its performance in a lab test scenario. First of all, we adopt the Discrete Cosine Transform (DCT) to transform a spatial-domain image into its spectral-domain equivalent. To reduce the computational complexity during the data-embedding process, addition allocation and subtraction data retrieval techniques are used. Moreover, channel coding is applied to overcome the data error caused by the optical wireless channel. In particular, robust turbo coding is used for error detection and correction. Afterward, we perform the experiments to validate the performance of the proposed system. After capturing the displayed image with a camera, data restoration is done using a deep learning technique. Extensive real-world experiments were performed considering various geometric distortions, noise, and different standard input images. As a result, we found that by increasing the transmit display image size (upsampling), the overall error rate can be reduced. In addition, real-world noise analysis is performed and it is notified that the actual noise is dominant in the low-frequency region of an image. The experimental results confirm the robust performance of the proposed DFC scheme and show that an error-free performance can be achieved up to a distance of 1m in the given lab test environment setting.

Shimming toolbox: An open-source software toolbox forB0and B1 shimming in MRI.

Introduce Shimming Toolbox ( https://shimming-toolbox.org), an open-source software package for prototyping new methods and performing static, dynamic, and real-time B0 shimming as well as B1 shimming experiments. Shimming Toolbox features various field mapping techniques, manual and automatic masking for the brain and spinal cord, B0 and B1 shimming capabilities accessible through a user-friendly graphical user interface. Validation of Shimming Toolbox was demonstrated in three scenarios: (i) B0 dynamic shimming in the brain at 7T using custom AC/DC coils, (ii) B0 real-time shimming in the spinal cord at 3T, and (iii) B1 static shimming in the spinal cord at 7T. The B0 dynamic shimming of the brain at 7T took about 10min to perform. It showed a 47% reduction in the standard deviation of the B0 field, associated with noticeable improvements in geometric distortions in EPI images. Real-time dynamic xyz-shimming in the spinal cord took about 5min and showed a 30% reduction in the standard deviation of the signal distribution. B1 static shimming experiments in the spinal cord took about 10min to perform and showed a 40% reduction in the coefficient of variation of the B1 field. Shimming Toolbox provides an open-source platform where researchers can collaborate, prototype and conveniently test B0 and B1 shimming experiments. Future versions will include additional field map preprocessing techniques, optimization algorithms, and compatibility across multiple MRI manufacturers.

Optimized flip angle schemes for the split acquisition offast spin-echo signals (SPLICE) sequence and application to diffusion-weighted imaging.

The diffusion-weighted SPLICE (split acquisition of fast spin-echo signals) sequence employs split-echo rapid acquisition with relaxation enhancement (RARE) readout to provide images almost free of geometric distortions. However, due to the varying T -weighting during k-space traversal, SPLICE suffers from blurring. This work extends a method for controlling the spatial point spread function (PSF) while optimizing the signal-to-noise ratio (SNR) achieved by adjusting the flip angles in the refocusing pulse train of SPLICE. An algorithm based on extended phase graph (EPG) simulations optimizes the flip angles by maximizing SNR for a flexibly chosen predefined target PSF that describes the desired k-space density weighting and spatial resolution. An optimized flip angle scheme and a corresponding post-processing correction filter which together achieve the target PSF was tested by healthy subject brain imaging using a clinical 1.5 T scanner. Brain images showed a clear and consistent improvement over those obtained with a standard constant flip angle scheme. SNR was increased and apparent diffusion coefficient estimates were more accurate. For a modified Hann k-space weighting example, considerable benefits resulted from acquisition weighting by flip angle control. The presented flexible method for optimizing SPLICE flip angle schemes offers improved MR image quality of geometrically accurate diffusion-weighted images that makes the sequence a strong candidate for radiotherapy planning or stereotactic surgery.

The Optimized Conformation Dynamics of the KcsA Filter as a Probe for Lateral Membrane Effects: A First Principle Based Femto-Sec Resolution MD Study.

We provide a high resolution, all-atom, femto-second molecular dynamics (MD) simulation of the passage of K+ ions and H2O molecules through the selectivity filter of the KcsA potassium ion channel, based on first principle physical methods. Our results show that a change in the length of the selectivity filter of as little as 3%, regardless of whether the filter is made longer or shorter, will reduce the K+ ion current by around 50%. In addition, further squeezing or stretching by about 9% can effectively stop the current. Our results demonstrate optimized conformational dynamics that associate an increased mobility of parts in the filter linings with a standard configuration, leading to maximized conduction rates that are highly sensitive to geometrical distortions. We discuss this latter aspect in relation to lateral membrane effects on the filter region of ion channels and the 'force from lipids' hypothesis.

Minimizing magnetic resonance image geometric distortion at 7 Tesla for frameless presurgical planning using skin-adhered fiducials.

7T MRI offers significant benefits to spatial and contrast resolution compared to lower field strengths. This superior image quality can help better delineate targets in stereotactic neurosurgical procedures; however, the potential for increased geometric distortions at 7T has impaired its widespread use for these applications. Image geometric distortions can be due to distortions of B0 arising from tissue magnetic susceptibility effects or inherent field inhomogeneities, and nonlinearity of the magnetic field gradients. The purpose of this study was to investigate the use of 7T MRI for neurosurgical frameless stereotactic navigation procedures. Image geometric distortions at the skin surface in 7T images were minimized and compared to results from clinical 3T frameless imaging protocols. A 3D-printed grid phantom filled with oil was designed to perform a fine calibration of the 7T imaging gradients, and an oil-filled head phantom with internal targets was used to determine ground truth (from computed tomography [CT]) positioning errors. Three volunteers and the head phantom were imaged consecutively at 3T and 7T. Ten skin-adhesive fiducial markers were placed on each subject's exposed skin surface at standard clinical placement locations for frameless procedures. Imaging sequences included MPRAGE (three bandwidths at 7T: 400, 690, and 1020Hz/pixel, and one at 3T: 400Hz/pixel), T2 SPACE, and T2 SPACE FLAIR acquisitions. An additional GRE field map was acquired on both scanners using a multi-echo GRE sequence. Custom Matlab code was used to perform additional distortion correction of the images using the unwrapped field maps. Fiducial localization was performed with 3D Slicer, with absolute fiducial positioning errors determined in phantom experiments following rigid registration to the CT images. For human experiments, 3T and 7T images were registered and relative differences in fiducial locations were compared using two-tailed paired t-tests. Phantom measurements at 7T yielded gradient distance scaling errors of 1.1%, 2.2%, and 1.0% along the x-, y-, and z-axes, respectively. These system miscalibrations were traced back to phantom manufacturing deviations in the sphericity of the vendor's gradient calibration phantom. Correction factors along each gradient axis were applied, and afterward, geometric distortions of less than 1mm were obtained in the 7T MR head phantom images for the 1020Hz/pixel bandwidth MPRAGE sequence. For the human subjects, four fiducial locations were excluded from the analysis due to patient positioning differences. Differences between 3T and 7T MPRAGE with low/medium/high bandwidth were 2.2/2.6/2.3mm, respectively, before the correction, reducing to 1.6/1.3/1.0mm after the correction (p<0.001). T2 SPACE and T2 SPACE FLAIR yielded a similar pattern when the correction was applied, decreasing from 2.1 to 0.8mm, and 2.6 to 1.0mm, respectively. 7T MRI can be used to perform frameless presurgical planning with skin-adhesive fiducials. Geometric distortions can be reduced to a clinically relevant level (errors<∼1mm) with no significant susceptibility-related distortions, by using high receiver bandwidth, ensuring gradients are properly calibrated, and placing skin fiducials in areas where distortions from patient positioning are minimal.

MRI data quality assessment for the RIN - Neuroimaging Network using the ACR phantoms

PurposeGenerating big-data is becoming imperative with the advent of machine learning. RIN-Neuroimaging Network addresses this need by developing harmonized protocols for multisite studies to identify quantitative MRI (qMRI) biomarkers for neurological diseases. In this context, image quality control (QC) is essential. Here, we present methods and results of how the RIN performs intra- and inter-site reproducibility of geometrical and image contrast parameters, demonstrating the relevance of such QC practice. MethodsAmerican College of Radiology (ACR) large and small phantoms were selected. Eighteen sites were equipped with a 3T scanner that differed by vendor, hardware/software versions, and receiver coils. The standard ACR protocol was optimized (in-plane voxel, post-processing filters, receiver bandwidth) and repeated monthly. Uniformity, ghosting, geometric accuracy, ellipse’s ratio, slice thickness, and high-contrast detectability tests were performed using an automatic QC script. ResultsMeasures were mostly within the ACR tolerance ranges for both T1- and T2-weighted acquisitions, for all scanners, regardless of vendor, coil, and signal transmission chain type. All measurements showed good reproducibility over time. Uniformity and slice thickness failed at some sites. Scanners that upgraded the signal transmission chain showed a decrease in geometric distortion along the slice encoding direction. Inter-vendor differences were observed in uniformity and geometric measurements along the slice encoding direction (i.e. ellipse’s ratio). ConclusionsUse of the ACR phantoms highlighted issues that triggered interventions to correct performance at some sites and to improve the longitudinal stability of the scanners. This is relevant for establishing precision levels for future multisite studies of qMRI biomarkers.

System-dependent image distortion related to gantry positions of a 0.35 T MRgRT: Characterization and the corresponding correction.

MR-guided radiotherapy with high accuracy treatment planning requires addressing MR imaging artifacts that originate from system imperfections. This work presents the characterization and corresponding correction of gantry-related imaging distortions including geometric distortion and isocenter shift in a 0.35 T magnetic resonance imaging (MRI)-guided radiotherapy (MRgRT) system using distortion vector fields (DVFs). Two phantoms, the magnetic resonance imaging distortion in 3D (MRID3D ) phantom and the Fluke phantom, along with a human volunteer were imaged at different gantry angles on a 0.35 T MR-Linac. The geometric distortion and isocenter shift were characterized for both phantom images. DVFs with a field of view extended beyond the physical boundary of the MRID3D phantom were extracted from images taken at 30° gantry angle increments, with vendor-provided distortion correction turned on and off (DstOff). These extended DVFs were then applied to the relevant phantom images to correct their geometric distortions and isocenter shift at the respective gantry angles. The extended DVFs produced from the MRID3D phantom were also applied to Fluke phantom and human MR images at their respective gantry angles. The resampled images were evaluated using structural similarity index measure (SSIM) comparison with the vendor corrected images from the MRgRT system. Geometric distortion with "mean (±SD) distortion" of 3.2±0.02, 2.9±0.02, and 1.8±0.01mm and isocenter shift (±SD) of 0.49±0.3, 0.05±0.2, and 0.01±0.03mm were present in the DstOff MRID3D phantom images in right-left (RL), anterior-posterior (AP), and superior-inferior (SI) directions, respectively. After resampling the originally acquired images by applying extended DVFs, the distortion was corrected to 0.18±0.02, 0.09±0.01, 0.15±0.01mm, and isocenter shift was corrected to 0.14±0.05, -0.02±0.04, and -0.07±0.05mm in RL, AP, and SI directions, respectively. The Fluke phantom average geometric distortion with "mean (±SD) distortion" of 2.7±0.1mm was corrected to 0.2±0. 1mm and the average isocenter shift (±SD) of 0.51±0.2mm, and 0.05±0.03 was corrected to -0.08±0.03mm, and -0.05±0.01 in RL and AP directions, respectively. SSIM (mean±SD) of the original images to resampled images was increased from 0.49±0.02 to 0.78±0.01, 0.45±0.02 to 0.75±0.01, and 0.86±0.25 to 0.98±0.08 for MRID3D phantom, Fluke phantom, and human MR images, respectively, for all the gantry angles compared to the vendor corrected images. The gantry-related MR imaging distortion including geometric distortion and isocenter shift was characterized and a corresponding correction was demonstrated using extended DVFs on 0.35 T MRgRT system. The characterized gantry-related isocenter shift can be combined with geometric distortion correction to provide a technique for the correction of the full system-dependent distortion in an MRgRT system.

Accelerated Diffusion-Weighted MR Image Reconstruction Using Deep Neural Networks

Under-sampling in diffusion-weighted imaging (DWI) decreases the scan time that helps to reduce off-resonance effects, geometric distortions, and susceptibility artifacts; however, it leads to under-sampling artifacts. In this paper, diffusion-weighted MR image (DWI-MR) reconstruction using deep learning (DWI U-Net) is proposed to recover artifact-free DW images from variable density highly under-sampled k-space data. Additionally, different optimizers, i.e., RMSProp, Adam, Adagrad, and Adadelta, have been investigated to choose the best optimizers for DWI U-Net. The reconstruction results are compared with the conventional Compressed Sensing (CS) reconstruction. The quality of the recovered images is assessed using mean artifact power (AP), mean root mean square error (RMSE), mean structural similarity index measure (SSIM), and mean apparent diffusion coefficient (ADC). The proposed method provides up to 61.1%, 60.0%, 30.4%, and 28.7% improvements in the mean AP value of the reconstructed images in our experiments with different optimizers, i.e., RMSProp, Adam, Adagrad, and Adadelta, respectively, as compared to the conventional CS at an acceleration factor of 6 (i.e., AF = 6). The results of DWI U-Net with the RMSProp, Adam, Adagrad, and Adadelta optimizers show 13.6%, 10.0%, 8.7%, and 8.74% improvements, respectively, in terms of mean SSIM with respect to the conventional CS at AF = 6. Also, the proposed technique shows 51.4%, 29.5%, 24.04%, and 18.0% improvements in terms of mean RMSE using the RMSProp, Adam, Adagrad, and Adadelta optimizers, respectively, with reference to the conventional CS at AF = 6. The results confirm that DWI U-Net performs better than the conventional CS reconstruction. Also, when comparing the different optimizers in DWI U-Net, RMSProp provides better results than the other optimizers.

Shape-Former: Bridging CNN and Transformer via ShapeConv for multimodal image matching

As with any data fusion task, the front-end of the pipeline for image fusion, aiming to collect multitudinous physical properties from multimodal images taken by different types of sensors, requires registering the overlapped content of two images via image matching. In other words, the accuracy of image matching will influence directly the subsequent fusion results. In this work, we propose a hybrid correspondence learning architecture, termed as Shape-Former, which is capable of solving matching problems such as multimodal, and multiview cases. Existing attempts have trouble capturing intricate feature interactions for seeking good correspondence, if the image pairs simultaneously suffer from geometric and radiation distortion. To address this, our key is to take advantage of convolutional neural network (CNN) and Transformer for enhancing structure consensus representation ability. Specifically, we introduce a novel ShapeConv so that CNN and Transformer can be generalized to sparse matches learning. Furthermore, we provide a robust soft estimation of outliers mechanism for filtering the response of outliers before capturing shape features. Finally, we also propose coupling multiple consensus representations to further solve the context conflict problems such as local ambiguity. Experiments with variety of datasets reveal that our Shape-Former outperforms state-of-the-art on multimodal image matching, and shows promising generalization ability to different types of image deformations.

The development of ultra-high field MRI guidance technology for neuronavigation.

Magnetic resonance imaging at 7T offers improved image spatial and contrast resolution for visualization of small brain nuclei targeted in neuromodulation. However, greater image geometric distortion and a lack of compatible instrumentation preclude implementation. In this report, the authors detail the development of a stereotactic image localizer and accompanying imaging sequences designed to mitigate geometric distortion, enabling accurate image registration and surgical planning of basal ganglia nuclei. Magnetization-prepared rapid acquisition with gradient echo (MPRAGE), fast gray matter acquisition T1 inversion recovery (FGATIR), T2-weighted, and T2*-weighted sequences were optimized for 7T in 9 human subjects to visualize basal ganglia nuclei, minimize image distortion, and maximize target contrast-to-noise and signal-to-noise ratios. Extracranial spatial distortions were mapped to develop a skull-contoured image localizer embedded with spherical silicone fiducials for improved MR image registration and target guidance. Surgical plan accuracy testing was initially performed in a custom-developed MRI phantom (n = 5 phantom studies) and finally in a human trial. MPRAGE and T2*-weighted sequences had the best measures among global measures of image quality (3.8/4, p < 0.0001; and 3.7/4, p = 0.0002, respectively). Among basal ganglia nuclei, FGATIR outperformed MPRAGE for globus pallidus externus (GPe) visualization (2.67/4 vs 1.78/4, p = 0.008), and FGATIR, T2-weighted imaging, and T2*-weighted imaging outperformed MPRAGE for substantia nigra visualization (1.44/4 vs 2.56/4, p = 0.04; vs 2.56/4, p = 0.04; vs 2.67/4, p = 0.003). Extracranial distortion was lower in the head's midregion compared with the base and apex ( 1.17-1.33 mm; MPRAGE and FGATIR, p < 0.0001; T2-weighted imaging, p > 0.05; and T2*-weighted imaging, p = 0.013). Fiducial placement on the localizer in low distortion areas improved image registration (fiducial registration error, 0.79-1.19 mm; p < 0.0001) and targeting accuracy (target registration error, 0.60-1.09 mm; p = 0.04). Custom surgical software and the refined image localizer enabled successful surgical planning in a human trial (fiducial registration error = 1.0 mm). A skull-contoured image localizer that accounts for image distortion is necessary to enable high-accuracy 7T imaging-guided targeting for surgical neuromodulation. These results may enable improved clinical efficacy for the treatment of neurological disease.

GSOR6 Presentation Time: 9:25 AM: Integrating a Novel GYN Brachytherapy Workflow Using In-Room CBCT Images with MR-LINAC Scans

<h3>Purpose</h3> Imaging capabilities within Radiation Oncology departments are increasing. Departments now have access to MRI imaging with MR-Linacs and designated brachytherapy mobile CBCT scanners. Utilization of these within-department imaging capabilities have the potential to improve clinical brachytherapy workflow. The purpose of this report is to investigate the feasibility of utilizing an MR-LINAC and a mobile CBCT scanner for patient imaging during HDR GYN brachytherapy. <h3>Materials and Methods</h3> To compare the spatial integrity of these imaging modalities, an HDR ring and tandem applicator was placed in a water phantom and imaged using a CT simulator (SOMATOM go.Open Pro, Siemens), 0.35T MR-LINAC (MRIdian, ViewRay) and a mobile CBCT scanner (ImagingRing, Elekta). The images acquired included a MR T2 weighted scan, a pelvis image guided brachytherapy CBCT acquisition, and a CT simulation. The images from the MR-LINAC and mobile CBCT scanner were each rigidly registered to CT-SIM images focusing on the applicator. Deviations in ring diameter, angle, and the position of the tip of the applicator was measured on each fusion. Additionally, a patient was imaged with the applicator inserted using the CT-Sim and the MR-LINAC systems. Physician drawn contours using these two modalities were compared to one another to investigate the benefits of incorporating MR-LINAC scans in the clinical HDR treatment planning process. <h3>Results</h3> The applicator was visible on each of the imaging modalities investigated. The deviation in the position of the applicator dimensions were less than 1mm on the MR-CT and CBCT-CT fusions. The analysis of the multimodality image fusions for the applicator revealed no large geometric distortions or loss of image quality when comparing the MR-CBCT image sets to MR-CT image sets. In patient scans, The MR planning image provided superior soft tissue contrast compared to the image acquired using the CT simulator. In this particular case, the superior soft tissue contrast provided by the MR scan provided more information for the physician for target delineation and resulted in a clinical decision to reduce the volume of the GTV. <h3>Conclusion</h3> This work presents a novel clinical workflow for HDR GYN brachytherapy using a mobile CBCT scanner and MR-LINAC for patient imaging. Incorporating the MR T2 scans into the clinical HDR brachytherapy workflow may aide in GYN brachytherapy target and OAR delineation. Additionally, the mobile CBCT scanner can reduce the challenges associated with patient setup and transportation between imaging and treatment locations. We found that the image quality and spatial resolution of MR and mobile CBCT based applicator images were clinically acceptable. A potential clinical workflow could involve using the MRIdian to obtain a planning image and contours the first fraction of treatment. Then on subsequent fractions the mobile CBCT scan could be fused to MR scans and used for daily applicator verification. For future work we will investigate a modified T2 sequence for MR guided brachytherapy to improve catheter reconstruction. Our work validates the clinical feasibility of using new technology for an MR-CBCT clinical workflow for HDR brachytherapy treatment planning.

Saturday, June 18, 20229:30 AM - 10:30 AM GPP06 Presentation Time: 9:30 AM: Image-Guided Cervical Cancer Brachytherapy: Summary of Consensus Recommendations from the Society for Abdominal Radiology and American Brachytherapy Society

<h3>Purpose</h3> To summarize recommendations regarding imaging guidance for cervical cancer brachytherapy implant placement from the Society of Abdominal Radiology (SAR) and American Brachytherapy Society (ABS). <h3>Materials and Methods</h3> A comprehensive literature search was conducted on PubMed for image-guided cervical cancer brachytherapy (BT) using radiography, ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI). Original research studies were included for evaluation if they included sensitivity and specificity of tumor detection, complication rates, or additional quantitative imaging results directly related to brachytherapy, such as geometric distortion measurements. The literature review was evaluated by an expert panel of members from the Society for Abdominal Radiology (SAR) and American Brachytherapy Society (ABS). These data were analyzed to determine an overall level of evidence for each recommendation and the subsequent strength of each claim. <h3>Results</h3> Three-dimensional (3D) imaging is recommended for treatment planning whenever feasible due to the rate of toxicities ≥ Grade 3 decreasing from between 0-13.5% with 2D planning to 0-5.8% with 3D planning. US guidance is highly recommended for tandem selection and insertion to reduce uterine perforation rates from 2.3-34%/insertion without US-guidance to 0-1.4%/insertion with US. US-guided interstitial needle placement is feasible when post-implant 3D imaging is available for treatment planning. Post-implant CT is recommended over orthogonal radiography to reduce genitourinary and gastrointestinal complications and evaluate proper applicator positioning. Tumor visualization is optimal on T2-weighted (T2w) MRI, which also provides improved specificity for assessment of parametrial invasion. CT-based treatment planning should refer to prior MRI for high risk-clinical target volume (HR-CTV) contouring, when available. Treatment planning on MRI is highly recommended for HR-CTV delineation, and post-applicator imaging should include at minimum both a 2D sagittal T2w and 3D axial T2w fast spin echo-based sequence. <h3>Conclusions</h3> Imaging-guidance for cervical brachytherapy implant placement is now standard-of-care. 3D imaging with MRI is highly recommended for treatment planning purposes, although CT-based planning also results in fewer complications as compared to 2D planning techniques. Ultrasound is useful for applicator placement, but application to treatment planning is limited.

Spatio-Temporal Context Based Adaptive Camcorder Recording Watermarking

Video watermarking technology has attracted increasing attention in the past few years, and a great deal of traditional and deep learning-based methods have been proposed. However, these existing methods usually suffer from the following two challenges: First, most algorithms cannot resist camcorder recording attack, which limits their practical application. Second, watermark embedding may cause substantial degradation of video quality. Through analyzing the unique distortions presented in the camcorder recording process, including geometric distortion, temporal sampling distortion, sensor distortion and processing distortion, this paper proposes a novel spatio-temporal context based adaptive camcorder recording watermarking scheme STACR. In STACR, considering the geometric distortion and video visual quality, we embed the watermark by constructing a spatio-temporal histogram and incorporate a content features based adaptive locating algorithm to select embedding blocks and embedding strengths. As for the temporal sampling attack, we put forward a watermark correlation-based synchronization algorithm and combine it with cross-validation. Moreover, to resist the sensor distortion, we design a local matching-based algorithm to improve the extraction accuracy. In addition, grouped and repeated embedding strategies are combined to cope with the processing distortion. Experimental results compared with the state-of-the-art show that the proposed scheme achieves high video quality and is robust to geometric attacks, compression, scaling, transcoding, recoding, frame rate changes and especially for camcorder recording.

Geometry, calibration, and robust centering procedures for refractive dome-port based imaging systems

Underwater imaging systems equipped with hemispherical ports can preserve the field of view and avert refraction when the camera and sphere centers coincide. Setting the camera at that center is a challenge, and deviation from this position introduces non-linear geometric distortions. These distortions have been treated by either computing the set of calibration parameters or by a more involved process of mechanically adjusting the camera center. Such strategies were approached empirically, and only recently have analytical system models begun to emerge. In this paper, we examine the geometry of dome-port-equipped imaging systems to develop a representation in which the non-linear ray trajectory is directly incorporated into the collinearity equations. The derivations apply for thin- and thick-layer interfaces and to the in-air setup. Our forms confirm the observations that when the camera and sphere center do not coincide, the system becomes axial. Yet, we improve on that observation by analytically demonstrating that with a slight modification to the camera parameters, the system model becomes central rather than the more involved form. Therefore, we not only link the axial realization with the commonly applied central form but also explain how to support this adaptation. Our representation and realizations translate to direct and optimal pose estimation and calibration forms that can be solved using standard protocols. To minimize distortions, we also propose a single-phase camera-centering solution. We demonstrate how our solution exhibits robustness to the initial camera placement and how the required parameters can be estimated linearly. Numerical and experimental evaluations support our calibration solution and demonstrate how our centering procedure captures the necessary displacement to a sub-tenth of a millimeter level.

Slice-direction geometric distortion evaluation and correction with reversed slice-select gradient acquisitions

Accurate spatial alignment of MRI data acquired across multiple contrasts in the same subject is often crucial for data analysis and interpretation, but can be challenging in the presence of geometric distortions that differ between acquisitions. It is well known that single-shot echo-planar imaging (EPI) acquisitions suffer from distortion in the phase-encoding direction due to B0 field inhomogeneities arising from tissue magnetic susceptibility differences and other sources, however there can be distortion in other encoding directions as well in the presence of strong field inhomogeneities. High-resolution ultrahigh-field MRI typically uses low bandwidth in the slice-encoding direction to acquire thin slices and, when combined with the pronounced B0 inhomogeneities, is prone to an additional geometric distortion in the slice direction as well. Here we demonstrate the presence of this slice distortion in high-resolution 7T EPI acquired with a novel pulse sequence allowing for the reversal of the slice-encoding gradient polarity that enables the acquisition of pairs of images with equal magnitudes of distortion in the slice direction but with opposing polarities. We also show that the slice-direction distortion can be corrected using gradient reversal-based method applying the same software used for conventional corrections of phase-encoding direction distortion.

Adaptive on Demand: Leveraging Cone Beam Computed Tomography-Based Adaptive Online Radiotherapy System as Simulation-Free Replan Platform

<h3>Purpose/Objective(s)</h3> Artificial intelligence powered cone beam computed tomography (CBCT) based online adaptive radiotherapy (ART) system offers a streamlined and efficient process for daily ART as the default. However, patients with gradual anatomy change from tumor response or weight loss may not significantly benefit from the daily ART. Instead, it will be more practical to adapt when changes are observed. In this work, we present a workflow and our early experience to utilize CBCT based ART system as a quick replan platform and the adapted plan is used for image guided radiotherapy (IGRT) until next adaptation. <h3>Materials/Methods</h3> Adaptive on demand is designed for patients treated with conventional fractionated dose and planned with conventional margins. The preplan is designed with 12-18 static IMRT fields with consideration of potential geometry/density change in beam arrangement and optimization to ensure the robustness of ART plan quality. Robustness evaluation is performed as needed. A plan revision process is required in the ART treatment planning system (TPS) to switch between adaptive and non-adaptive fractions in a treatment course. The plan is converted to the adaptive treatment upon physician's request. After each ART, the adapted plan is imported to TPS and physicist checks the quality of the synthetic CT (SCT), which is a deformed planning CT to CBCT geometry, and determines SCT/CBCT to be used as reference for the upcoming IGRT fractions. <h3>Results</h3> A total of 23 HN patients and 13 lung patients were treated with ART on demand from 09/2021-01/2022. 110 on-demand ART fractions analyzed. On average, each HN/lung patient received 1.9 (range 1-6)/5.2 (range 4-6) ART and 90.6%/85.3% frequency that the adapted plan was selected for treatment. Overall, the adapted plans show statistically significant improvements in tumor coverage and dose conformity comparing to original plan and meet the OAR objectives. Detailed dosimetric benefits are presented in other abstracts. Given the SCT is generated via deformable registration, the distortion of the SCT was observed in some cases. While dosimetric impact are negligible for the majority of cases, the geometric distortions of bony anatomy can lead to setup difficulty for the IGRT fractions and two patients were rescanned due to this reason. Cutting out the mask is recommended when it becomes loose to avoid SCT picking up mask as body and results in unsatisfactory planning target volume cropping from skin. The conversion to adaptive fraction requires 15 minutes while setting up adapted plan for IGRT fraction takes 25 minutes. Physician's time at console time is 18/14 minutes for HN and lung. <h3>Conclusion</h3> Leveraging CBCT based ART system as replan platform is feasible and satisfactory in plan quality. Physicist check on the SCT quality is crucial to prevent potential target generation uncertainties and setup error. This process significantly improved the turnaround time for replan and saves a trip for rescan.

Comparison of TGSE-BLADE DWI, RESOLVE DWI, and SS-EPI DWI in healthy volunteers and patients after cerebral aneurysm clipping

Diffusion-weighted magnetic resonance imaging is prone to have susceptibility artifacts in an inhomogeneous magnetic field. We compared distortion and artifacts among three diffusion acquisition techniques (single-shot echo-planar imaging [SS-EPI DWI], readout-segmented EPI [RESOLVE DWI], and 2D turbo gradient- and spin-echo diffusion-weighted imaging with non-Cartesian BLADE trajectory [TGSE-BLADE DWI]) in healthy volunteers and in patients with a cerebral aneurysm clip. Seventeen healthy volunteers and 20 patients who had undergone surgical cerebral aneurysm clipping were prospectively enrolled. SS-EPI DWI, RESOLVE DWI, and TGSE-BLADE DWI of the brain were performed using 3 T scanners. Distortion was the least in TGSE-BLADE DWI, and lower in RESOLVE DWI than SS-EPI DWI near air–bone interfaces in healthy volunteers (P < 0.001). Length of clip-induced artifact and distortion near the metal clip were the least in TGSE-BLADE DWI, and lower in RESOLVE DWI than SS-EPI DWI (P < 0.01). Image quality scores for geometric distortion, susceptibility artifacts, and overall image quality in both healthy volunteers and patients were the best in TGSE-BLADE DWI, and better in RESOLVE DWI than SS-EPI DWI (P < 0.001). Among the three DWI sequences, image quality was the best in TGSE-BLADE DWI in terms of distortion and artifacts, in both healthy volunteers and patients with an aneurysm clip.