Small Field Of View Research Articles

Pediatric evaluations for deep learning CT denoising.

Deep learning (DL) CT denoising models have the potential to improve image quality for lower radiation dose exams. These models are generally trained with large quantities of adult patient image data. However, CT, and increasingly DL denoising methods, are used in both adult and pediatric populations. Pediatric body habitus and size can differ significantly from adults and vary dramatically from newborns to adolescents. Ensuring that pediatric subgroups of different body sizes are not disadvantaged by DL methods requires evaluations capable of assessing performance in each subgroup. To assess DL CT denoising in pediatric and adult-sized patients, we built a framework of computer simulated image quality (IQ) control phantoms and evaluation methodology. The computer simulated IQ phantoms in the framework featured pediatric-sized versions of standard CatPhan 600 and MITA-LCD phantoms with a range of diameters matching the mean effective diameters of pediatric patients ranging from newborns to 18 years old. These phantoms were used in simulating CT images that were then inputs for a DL denoiser to evaluate performance in different sized patients. Adult CT test images were simulated using standard-sized phantoms scanned with adult scan protocols. Pediatric CT test images were simulated with pediatric-sized phantoms and adjusted pediatric protocols. The framework's evaluation methodology consisted of denoising both adult and pediatric test images then assessing changes in image quality, including noise, image sharpness, CT number accuracy, and low contrast detectability. To demonstrate the use of the framework, a REDCNN denoising model trained on adult patient images was evaluated. To validate that the DL model performance measured with the proposed pediatric IQ phantoms was representative of performance in more realistic patient anatomy, anthropomorphic pediatric XCAT phantoms of the same age range were also used to compare noise reduction performance. Using the proposed pediatric-sized IQ phantom framework, size differences between adult and pediatric-sized phantoms were observed to substantially influence the adult trained DL denoising model's performance. When applied to adult images, the DL model achieved a 60% reduction in noise standard deviation without substantial loss in sharpness in mid or high spatial frequencies. However, in smaller phantoms the denoising performance dropped due to different image noise textures resulting from the smaller field of view (FOV) between adult and pediatric protocols. In the validation study, noise reduction trends in the pediatric-sized IQ phantoms were found to be consistent with those found in anthropomorphic phantoms. We developed a framework of using pediatric-sized IQ phantoms for pediatric subgroup evaluation of DL denoising models. Using the framework, we found the performance of an adult trained DL denoiser did not generalize well in the smaller diameter phantoms corresponding to younger pediatric patient sizes. Our work suggests noise texture differences from FOV changes between adult and pediatric protocols can contribute to poor generalizability in DL denoising and that the proposed framework is an effective means to identify these performance disparities for a given model.

Indications and use of cone beam computed tomography in children and young individuals in a university-based dental hospital

BackgroundThe aim of this study was to evaluate the indications of cone beam computed tomography (CBCT) in children and young individuals in a university-based dental hospital and their association with age, gender and field of view.Methods7131 CBCT scans, taken during 3-year period, were reviewed and a total of 649 pediatric patients (0–18 years) with complete request forms were included. Data related to gender, age, referring department, CBCT indications, field of view (FOV), region of interest (ROI), need for re-exposure and patients received more than one CBCT examination were recorded.ResultsThe mean age was 13.57 ± 3.52 years and “malocclusion and dentofacial anomaly” (28.7%) was the most common clinical indication. Facial trauma, dental trauma and supernumerary tooth in males; “malocclusion and dentofacial anomaly” and implant planning in females were recorded more frequently compared to other gender. Maxilla was the most frequently monitored ROI (35.1%) for patients. Small (≤ 10 cm) FOV was preferred in 58.1% of all patients. Large FOV was selected in the majority of patients who underwent CBCT scan for “malocclusion and dentofacial anomaly” (89.6%). The repeated scans constituted 2.3% of patients and 105 patients (16.2%) underwent multiple CBCT scans on different dates for mainly orthodontic follow-up.ConclusionsThe justification of CBCT scans was not fully compatible with current guidelines and mainly larger FOV was preferred. The number of CBCT examination in children and young individuals tends to increase.Trial registration numberNot applicable.

Incidental findings in cone beam computed tomography (CBCT) scans for implant treatment planning: a retrospective study of 404 CBCT scans

ObjectivesTo investigate the prevalence of incidental findings and need for further dental treatment and analyse the influence of size of field-of-view (FOV) and age in cone beam computed tomography (CBCT) for pre-implant planning.Methods404 CBCT scans were examined retrospectively for incidental findings and need for further dental treatment. Incidental finding-frequencies and need for further treatment were assessed for different age (< 40 years, 40–60 years, > 60 years) and FOV groups (small, medium, large). Intraexaminer and interexaminer agreements were evaluated.ResultsIn 82% of the scans at least one incidental finding was found, with a total of 766 overall. More incidental findings were found in scans with large FOV (98% vs. 72%, OR = 22.39 large vs. small FOV, p < 0.0001) and in scans of patients > 60 years (OR = 5.37 patient’s age > 60 years vs. < 40 years, p = 0.0003). Further dental treatment due to incidental findings was needed in 31%. Scans with large FOV were more likely to entail further treatment (OR = 3.55 large vs. small FOV, p < 0.0001). Partial edentulism and large FOV were identified as risk factors for further treatment (p = 0.0003 and p < 0.0001). Further referral of the patient based on incidental findings was judged as indicated in 5%. Intra- and inter-examiner agreements were excellent (kappa = 0.944/0.805).ConclusionsA considerable number of incidental findings with need for further dental treatment was found in partially edentulous patients and in patients > 60 years. In pre-implant planning of elderly patients, the selection of large FOV CBCT scans, including dentoalveolar regions not X-rayed recently, help to detect therapeutically relevant incidental findings.

Adding a Small Field of View for Increased Resolution in Contouring: An Effective and Quick Method

Image resolution is paramount when contouring complex anatomy, as in head and neck planning. It is notable that when diagnostic radiologists perform a computed tomography scan of the neck, they always use a small field of view because it gives the best image resolution. When planning for radiation treatment, however, it is also necessary to have a large field of view to provide a comprehensive external contour that allows for radiation dose calculation. We present a simple method to obtain both small and large fields of view at the time of computed tomography simulation.

Global cone-beam computed tomography adoption, usage and scan interpretation preferences of dentists and endodontists.

This study investigated the adoption of cone-beam computed tomography (CBCT) by dentists and endodontists around the world, including their preferences in endodontic CBCT usage. An online questionnaire surveyed dental association members in Australia and New Zealand, and endodontic association members in Australia, Britain, Canada, Italy, New Zealand and the USA, about their CBCT training history, considerations in acquisition/interpretation, access to and usage of CBCT, preferred scan interpreter, and preferred endodontic scan settings. Data were analysed with Chi-squared, independent sample t-tests, Cochran's Q and McNemar's tests. Responses from 578 endodontic specialists or postgraduates (Group E) and 185 non-endodontic dentists (Group NE) were included. Continuing professional education (CPE) was the most common source of CBCT training (69.2%). Factors considered in CBCT acquisition/interpretation included beam hardening (75.4%), radiation exposure (61.1%) and patient movement (58.3%). Group E reported higher CBCT usage (90.8%) than Group NE (45.4%, p < .001) and greater workplace access to CBCT (81.1% vs. 25.9%, p < .001). Scans were interpreted by the respondent in most workplace scans (83.3%) and externally taken scans (60.5%); Group E were significantly more likely to interpret themselves than Group NE. Small field of view (83.6%) and high resolution (86.6%) were most preferred as settings for endodontic CBCTs; Group NE were less likely to choose these settings. There were some geographic variations within Group E. CBCT training was most commonly acquired via CPE. Endodontic respondents reported very high CBCT usage and access in the workplace. There are educational implications regarding CBCT limitations, appropriate applications and interpretation.

Presence of subchondral fracture in cases diagnosed as transient osteoporosis of the hip: a retrospective independent reader-based study.

Transient osteoporosis of the hip (TOH) is an uncommon, typically self-limited diagnosis of uncertain etiology. We hypothesize that TOH represents an underlying subchondral fracture, and a discrete fracture line can often be detected on high-resolution MRI. A retrospective PACS query identified patients meeting imaging criteria for TOH with intense bone marrow edema (BME) in the femoral head on MRI. Those with poor quality studies, other underlying pathologies, or antecedent trauma were excluded. Three musculoskeletal radiologists independently reviewed each case for presence of a definite subchondral fracture line on small field of view (FOV) MR images of the affected hip. Extent of BME, reciprocal acetabular BME, and joint effusion size were also recorded. Binomial logistic regression was performed to determine statistically significant predictors of subchondral fracture. Fifty patients met inclusion criteria (29 females, 0 pregnant). Mean age was 62±12 years (range 35-84). Average duration of symptoms before MRI was 102±135 days. Ten patients had bone densitometry within 2 years of MRI, six demonstrating osteopenia or osteoporosis. Subchondral fractures were unanimously identified in 44/50 (88%). Interclass correlation coefficient with absolute agreement was 0.73, 95% CI (0.57-0.84), indicating near-excellent agreement. Most cases demonstrated a large joint effusion (23/50, 46%) and acetabular BME (31/50, 62%). Increasing size of joint effusion was a statistically significant predictor of subchondral fracture (p=0.05), with 6.9 higher odds. There was a strong correlation with osteopenia/osteoporosis and fracture (p<0.001). Discrete subchondral fractures were identified unanimously on small FOV imaging in the majority of TOH cases.

Miniature line-scanned dual-axis confocal microscope for versatile clinical use.

A miniature optical-sectioning fluorescence microscope with high sensitivity and resolution would enable non-invasive and real-time tissue inspection, with potential use cases including early disease detection and intraoperative guidance. Previously, we developed a miniature MEMS-based dual-axis confocal (DAC) microscope that enabled video-rate optically sectioned in vivo microscopy of human tissues. However, the device's clinical utility was limited due to a small field of view, a non-adjustable working distance, and a lack of a sterilization strategy. In our latest design, we have made improvements to achieve a 2x increase in the field of view (600 × 300 µm) and an adjustable working distance range of 150 µm over a wide range of excitation/emission wavelengths (488-750 nm), all while maintaining a high frame rate of 15 frames per second (fps). Furthermore, the device is designed to image through a disposable sterile plastic drape for convenient clinical use. We rigorously characterize the performance of the device and show example images of ex vivo tissues to demonstrate the optical performance of our new design, including fixed mouse skin and human prostate, as well as fresh mouse kidney, mouse intestine, and human head and neck surgical specimens with corresponding H&E histology. These improvements will facilitate clinical testing and translation.

Welding defects on new energy batteries based on 2D pre-processing and improved-region-growth method in the small field of view

The assessment of welding quality in battery shell production is a crucial aspect of battery production. Battery surface reconstruction can inspect the quality of the weld instead of relying on human inspection. This paper proposes a defect detection method in the small field of view based on 2D pre-processing and an improved-region-growth method. A novel approximation-based, high-precision, and simple operation method for line structure optical plane calibration under small field of view is presented, with a measurement error within 0.01 mm. By pre-processing the line scan 2D images, the defect location distribution is obtained, and then the images near the abnormal points are reconstructed in third dimensional (3D). The proposed method enables the extraction of the morphology, size, and other information of the defects with high accuracy. The results of various defect detection experiments demonstrate the stable and reliable performance of the system. The experimental results of defect recognition rate are over 95.3% for defects above 0.5 mm in diameter, and the inspection time is less than 1/2 of the direct 3D defect inspection. Overall, this method has proven to be highly effective in the assessment of welding quality in new energy battery production.

An atypical anatomy of permanent mandibular second molar with five roots.

Especially in molars that may have sometimes aberrant additional root canals, the complexity of tooth internal morphology in individual cases sometimes does not match to admitted classification rules and underlines the risk of missed anatomy during the endodontic management. To our knowledge, a permanent mandibular second molar with independent five roots, three mesial and two distal, each of them harboring a single canal, was not yet reported. Despite the treatment difficulties this tooth could be successfully approached by using dental operative microscope and cone-beam computed tomography (CBCT) with small field of view. Though CBCT is not a routine imagistic examination, in case of atypical tooth anatomy aiming to establish adequate diagnosis and treatment plan, the successful clinical outcome prevails over the irradiation dose.

End-to-end memory-efficient reconstruction for cone beamCT.

Cone beam computed tomography (CBCT) plays an important role in many medical fields nowadays. Unfortunately, the potential of this imaging modality is hampered by lower image quality compared to the conventional CT, and producing accurate reconstructions remains challenging. A lot of recent research has been directed towards reconstruction methods relying on deep learning, which have shown great promise for various imaging modalities. However, practical application of deep learning to CBCT reconstruction is complicated by several issues, such as exceedingly high memory costs of deep learning methods when working with fully 3D data. Additionally, deep learning methods proposed in the literature are often trained and evaluated only on data from a specific region of interest, thus raising concerns about possible lack of generalization to other regions. In this work, we aim to address these limitations and propose LIRE: a learned invertible primal-dual iterative scheme for CBCTreconstruction. LIRE is a learned invertible primal-dual iterative scheme for CBCT reconstruction, wherein we employ a U-Net architecture in each primal block and a residual convolutional neural network (CNN) architecture in each dual block. Memory requirements of the network are substantially reduced while preserving its expressive power through a combination of invertible residual primal-dual blocks and patch-wise computations inside each of the blocks during both forward and backward pass. These techniques enable us to train on data with isotropic 2 mm voxel spacing, clinically-relevant projection count and detector panel resolution on current hardware with 24 GBvideo random access memory (VRAM). Two LIRE models for small and for large field-of-view (FoV)setting were trained and validated on a set of 260 + 22 thorax CT scans and tested using a set of 142 thorax CT scans plus an out-of-distribution dataset of 79 head and neck CT scans. For both settings, our method surpasses the classical methods and the deep learning baselines on both test sets. On the thorax CT set, our method achieves peak signal-to-noise ratio (PSNR) of 33.84 ± 2.28 for the small FoV setting and 35.14 ± 2.69 for the large FoV setting; U-Net baseline achieves PSNR of 33.08 ± 1.75 and 34.29 ± 2.71 respectively. On the head and neck CT set, our method achieves PSNR of 39.35 ± 1.75 for the small FoV setting and 41.21 ± 1.41 for the large FoV setting; U-Net baseline achieves PSNR of 33.08 ± 1.75 and 34.29 ± 2.71 respectively. Additionally, we demonstrate that LIRE can be finetuned to reconstruct high-resolution CBCT data with the same geometry but 1 mm voxel spacing and higher detector panel resolution, where it outperforms the U-Net baseline aswell. Learned invertible primal-dual schemes with additional memory optimizations can be trained to reconstruct CBCT volumes directly from the projection data with clinically-relevant geometry and resolution. Such methods can offer better reconstruction quality and generalization compared to classical deep learning baselines.

Cross Correlation of Pencil-beam Galaxy Surveys and Line-intensity Maps: An Application of the James Webb Space Telescope

Line-intensity mapping (IM) experiments seek to perform statistical measurements of large-scale structure with spectral lines such as 21 cm, CO, and Lyα. A challenge in these observations is to ensure that astrophysical foregrounds, such as galactic synchrotron emission in 21 cm measurements, are properly removed. One method that has the potential to reduce foreground contamination is to cross correlate with a galaxy survey that overlaps with the IM volume. However, telescopes sensitive to high-redshift galaxies typically have small field of views compared to IM surveys. Thus, a galaxy survey for cross correlation would necessarily consist of pencil beams that sparsely fill the IM volume. In this paper, we develop the formalism to forecast the sensitivity of cross correlations between IM experiments and pencil-beam galaxy surveys. We find that a random distribution of pencil beams leads to very similar overall sensitivity as a lattice spaced across the IM survey and derive a simple formula for random configurations that agrees with the Fisher matrix formalism. We explore examples of combining high-redshift James Webb Space Telescope (JWST) observations with both an SPHEREx-like Lyα IM survey and a 21 cm experiment based on the Hydrogen Epoch of Reionization Array (HERA). We find that the JWST-SPHEREx case is promising, leading to a total signal-to-noise ratio of ∼5 after 100 total hours of JWST (at z = 7). We find that HERA is not well-suited for this approach owing to its drift-scan strategy, but that a similar experiment that can integrate down on one field could be.

An innovative multi-modal retinal imaging system for in vivo retinal detection in small animals.

This paper presents an innovative retinal imaging system tailored for in vivo fundus detection in small animals. This system integrates Scanning Laser Ophthalmoscopy (SLO) and optical Coherence Tomography (OCT) techniques, enabling the simultaneous generation of images from various modalities, including SLO reflectance, SLO fluorescein angiogram, OCT, and OCT angiogram. The existing multi-modal retinal imaging systems generally encounter limitations such as the inability to detect peripheral lesion areas attributed to small Field of View (FOV) design and susceptibility to sample motion due to slow data acquisition speed. To address these challenges, it's essential to underscore that this proposed system offers a range of notable advantages, including its compact design, the capacity for widefield imaging with a FOV of up to 100°, and a rapid OCT A-scan rate of 250 kHz, notably exceeding the capabilities of pre-existing multi-modal retinal imaging systems. Validation of the system involved imaging the eyes of normal wild-type mice and diseased mice afflicted with retinal detachment and choroidal neovascularization (CNV). The favorable imaging results demonstrate the system's reliability in identifying retinal lesions in small animals.

Detector system challenges of the wide‐field spectroscopic survey telescope (WST)

AbstractThe wide‐field spectroscopic survey telescope (WST) is proposed to become the next large optical/near infrared facility for the European southern observatory (ESO) once the extremely large telescope (ELT) has become operational. While the latter is optimized for unprecedented sensitivity and adaptive‐optics assisted image quality over a small field of view, WST addresses the need for large survey volumes in spectroscopy with the light‐collecting power of a 10‐m class telescope. Its unique layout will feature the combination of multi‐object and integral field spectroscopy simultaneously. For the intended capacity of this layout, a very large number of detectors are needed. The complexity of the detector systems presents a number of challenges that are discussed with a focus on novel approaches and innovative detector designs that can be expected to emerge over the anticipated 20‐year timeline of this project.

Wide field-of-view fluorescence imaging for organ-level lineage tracing of rare intestinal stem cell populations.

Lineage tracing using fluorescent reporters is a common tool for monitoring the expression of genes and transcription factors in stem cell populations and their progeny. The zinc-binding protein 89 (ZBP-89/Zfp148 mouse gene) is a transcription factor that plays a role in gastrointestinal (GI) stem cell maintenance and cellular differentiation and has been linked to the progression of colon cancer. While lineage tracing is a useful tool, it is commonly performed with high-magnification microscopy on a small field of view within tissue sections, thereby limiting the ability to resolve reporter expression at the organ level. Furthermore, this technique requires extensive tissue processing, which is time consuming and requires euthanizing the animal. Further knowledge could be elucidated by measuring the expression of fluorescent reporters across entire organs with minimal tissue processing. We present the application of wide-field fluorescence imaging for whole-organ lineage tracing of an inducible Zfp148-tdTomato-expressing transgenic mouse line to assess the expression of ZBP-89/Zfp148 in the GI tract. We measured tdTomato fluorescence in ex vivo organs at time points between 24h and 6 months post-induction. Fluctuations in tdTomato expression were validated by fluorescence microscopy of tissue sections. Quantification of the wide field-of-view images showed a statistically significant increase in fluorescent signal across the GI tract between transgenic mice and littermate controls. The results also showed a gradient of decreasing reporter expression from proximal to distal intestine, suggesting a higher abundance of ZBP-89 expressing stem cells, or higher expression of ZBP-89 within the stem cells, in the proximal intestine. We demonstrate that wide-field fluorescence imaging is a valuable tool for monitoring whole-organ expression of fluorescent reporters. This technique could potentially be applied in vivo for longitudinal assessment of a single animal, further enhancing our ability to resolve rare stem cell lineages spatially and temporally.

Block attention network: A lightweight deep network for real-time semantic segmentation of road scenes in resource-constrained devices

Deep-learning-based semantic segmentation networks typically incorporate object classification networks in their backbone. This leads to a loss of context because classification networks have a smaller field of view. The architecture has been extended to recover context with additional downsampling feature maps, a parallel context branch, or pyramid pooling modules after the backbone. However, these extensions increase multiply–accumulate operations and memory requirements, thus, making them unsuitable for resource-constrained devices. To overcome this limitation, a novel convolutional building block with attention-based context guidance is proposed. The block is repeated to build an efficient encoder–decoder network. Our network runs in real-time, has a lightweight design with only 0.72 Million parameters, and achieves 70.1%, and 66.3% mean intersection-over-union scores on the highly competitive Cityscapes and CamVid datasets, respectively. An efficient decoder is also designed to replace other semantic segmentation network decoders with minimal performance loss. The performance measures on mobile platforms show that our network suits resource-constrained devices. Further, experimental results show that the proposed method can optimally balance the model size-inference speed and segmentation accuracy.

Comparison of Performance of Micro-Computed Tomography (Micro-CT) and Synchrotron Radiation CT in Assessing Coronary Stenosis Caused by Calcified Plaques in Coronary Artery Phantoms

Synchrotron-radiation-computed tomography (SRCT) allows more accurate calcified plaque and coronary stenosis assessment as a result of its superior spatial resolution; however, typical micro-computed tomography (micro-CT) systems have even higher resolution. The purpose of this study was to compare the performance of high-resolution micro-CT with SRCT in the assessment of calcified plaques and a previously published dataset of coronary stenosis assessment. This experimental study involved micro-CT scanning of three-dimensional printed coronary artery models with calcification in situ used in our previously published SRCT study on coronary stenosis assessment. Measurements of coronary stenosis utilizing both modalities were compared using a paired sample t-test. The degrees of stenosis measured on all but one micro-CT dataset were statistically significantly lower than the corresponding SRCT measurements reported in our previous paper (p &lt; 0.0005–0.05). This indicates that the superior spatial resolution of micro-CT was able to further reduce over-estimation of stenosis caused by extensive calcification of coronary arteries and, hence, false positive results. Our results showed that the high-resolution micro-CT used in this study outperformed the Australian Synchrotron SRCT in both calcified plaque and coronary stenosis assessment. These findings will become clinically important for cardiovascular event prediction and enable reclassification of individuals with low and intermediate risk into appropriate risk categories when the technical challenges of micro-CT in clinical practice such as the small field of view and demanding on image processing power are addressed.

An Overview of FAST Real-time Fast Radio Burst Searching System

In this paper, we report a real-time Fast Radio Burst (FRB) searching system that has been successfully implemented with the 19 beam receiver of the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The relatively small field of view of FAST makes the search for new FRBs challenging, but its high sensitivity significantly improves the accuracy of FRB localization and enables the detection of high-precision neutral hydrogen absorption lines generated by FRBs. Our goal is to develop an FRB searching system capable of real-time detection of FRBs that allows high-time resolution spectro-temporal studies among the repeated bursts, as well as detailed investigations of these bursts and exploration of FRB progenitor models. The data from each beam of the 19-beam receiver are fed into a high-performance computing node server, which performs real-time searches for pulses with a wide dispersion measure (DM) range of 20–10,000 pc cm−3 with step efficiency of 25% in real time. Then, the head node server aggregates all the candidate signals from each beam within a given time, determining their authenticity based on various criteria, including arrival time, pulse width, signal-to-noise ratio and coincidence patterns among the 19 beams. Within the 1.05–1.45 GHz operating bandwidth of the FAST 19 beam receiver, the system achieves a frequency resolution of 122.07 kHz and a time resolution of 270.336 μs. Subsequently, our team detected a series of bursts with a DM of 566 on 2019 August 30 confirming them as FRB 121102. The FRB searching system enables the 19-beam receiver of FAST to detect repeated/one-off pulses/bursts in real time.

A transformer-based dual-domain network for reconstructing FOV extended cone-beam CT images from truncated sinograms in radiation therapy

Background and objectiveCone-beam computed tomography (CBCT) is widely used in clinical radiotherapy, but its small field of view (sFOV) limits its application potential. In this study, a transformer-based dual-domain network (dual_swin), which combined image domain restoration and sinogram domain restoration, was proposed for the reconstruction of complete CBCT images with extended FOV from truncated sinograms. MethodsThe planning CT images with large FOV (LFOV) of 330 patients who received radiation therapy were collected. The synthetic CBCT (sCBCT) images with LFOV were generated from CT images by the trained cycleGAN network, and CBCT images with sFOV were obtained through forward projection, projection truncation, and filtered back projection (FBP), comprising the training and test data. The proposed dual_swin includes sinogram domain restoration, image domain restoration, and FBP layer, and the swin transformer blocks were used as the basic feature extraction module in the network to improve the global feature extraction ability. The proposed dual_swin was compared with the image domain method, the sinogram domain method, the U-Net based dual domain network (dual_Unet), and the traditional iterative reconstruction method based on prior image and conjugate gradient least-squares (CGLS) in the test of sCBCT images and clinical CBCT images. The HU accuracy and body contour accuracy of the predicted images by each method were evaluated. ResultsThe images generated using the CGLS method were fuzzy and obtained the lowest structural similarity (SSIM) among all methods in the test of sCBCT and clinical CBCT images. The predicted images by the image domain methods are quite different from the ground truth and have low accuracy on HU value and body contour. In comparison with image domain methods, sinogram domain methods improved the accuracy of HU value and body contour but introduced secondary artifacts and distorted bone tissue. The proposed dual_swin achieved the highest HU and contour accuracy with mean absolute error (MAE) of 23.0 HU, SSIM of 95.7%, dice similarity coefficient (DSC) of 99.6%, and Hausdorff distance (HD) of 4.1 mm in the test of sCBCT images. In the test of clinical patients, images that were predicted by dual_swin yielded MAE, SSIM, DSC, and HD of 38.2 HU, 91.7%, 99.0%, and 5.4 mm, respectively. The predicted images by the proposed dual_swin has significantly higher accuracy than the other methods (P < 0.05). ConclusionsThe proposed dual_swin can accurately reconstruct FOV extended CBCT images from the truncated sinogram to improve the application potential of CBCT images in radiotherapy.

Sample Variance in Cosmological Observations with a Narrow Field of View

Surveys with a narrow field of view can play an important role in probing cosmology, but inferences from these surveys suffer from large sample variance, arising from random fluctuations around the cosmic mean. The standard method for computing the sample variance is based on two key approximations: treating perturbations linearly and the survey geometry as a box. We demonstrate that it can lead to a significant underestimate of the sample variance in narrow surveys. We present a new method for accurately computing the sample variance and apply our method to the recent observations of the warm–hot intergalactic medium (WHIM) based on spectroscopic measurements of blazars. We find that the sample variances in these surveys are significantly larger than the quoted measurement errors; for example, the cosmic mean baryon density contained in the WHIM could be lower by 54% at 1σ fluctuation than estimated in one observation. Accurately quantifying the sample variance is essential in deriving correct interpretations of the measurements in surveys with a small field of view.

Multiscale Stamps for Real-time Classification of Alert Streams

In recent years, automatic classifiers of image cutouts (also called “stamps”) have been shown to be key for fast supernova discovery. The Vera C. Rubin Observatory will distribute about ten million alerts with their respective stamps each night, enabling the discovery of approximately one million supernovae each year. A growing source of confusion for these classifiers is the presence of satellite glints, sequences of point-like sources produced by rotating satellites or debris. The currently planned Rubin stamps will have a size smaller than the typical separation between these point sources. Thus, a larger field-of-view stamp could enable the automatic identification of these sources. However, the distribution of larger stamps would be limited by network bandwidth restrictions. We evaluate the impact of using image stamps of different angular sizes and resolutions for the fast classification of events (active galactic nuclei, asteroids, bogus, satellites, supernovae, and variable stars), using data from the Zwicky Transient Facility. We compare four scenarios: three with the same number of pixels (small field of view with high resolution, large field of view with low resolution, and a multiscale proposal) and a scenario with the full stamp that has a larger field of view and higher resolution. Compared to small field-of-view stamps, our multiscale strategy reduces misclassifications of satellites as asteroids or supernovae, performing on par with high-resolution stamps that are 15 times heavier. We encourage Rubin and its Science Collaborations to consider the benefits of implementing multiscale stamps as a possible update to the alert specification.