A Voxel-Based Approach for Imaging Voids in Three-Dimensional Point Clouds

Geographically accurate scene models have enormous potential beyond that of just simple visualizations in regard to automated scene generation. In recent years, thanks to ever increasing computational efficiencies, there has been significant growth in both the computer vision and photogrammetry communities pertaining to automatic scene reconstruction from multiple-view imagery. The result of these algorithms is a three-dimensional (3D) point cloud which can be used to derive a final model using surface reconstruction techniques. However, the fidelity of these point clouds has not been well studied, and voids often exist within the point cloud. Voids exist in texturally difficult areas, as well as areas where multiple views were not obtained during collection, constant occlusion existed due to collection angles or overlapping scene geometry, or in regions that failed to triangulate accurately. It may be possible to fill in small voids in the scene using surface reconstruction or hole-filling techniques, but this is not the case with larger more complex voids, and attempting to reconstruct them using only the knowledge of the incomplete point cloud is neither accurate nor aesthetically pleasing. A method is presented for identifying voids in point clouds by using a voxel-based approach to partition the 3D space. By using collection geometry and information derived from the point cloud, it is possible to detect unsampled voxels such that voids can be identified. This analysis takes into account the location of the camera and the 3D points themselves to capitalize on the idea of free space, such that voxels that lie on the ray between the camera and point are devoid of obstruction, as a clear line of sight is a necessary requirement for reconstruction. Using this approach, voxels are classified into three categories: occupied (contains points from the point cloud), free (rays from the camera to the point passed through the voxel), and unsampled (does not contain points and no rays passed through the area). Voids in the voxel space are manifested as unsampled voxels. A similar line-of-sight analysis can then be used to pinpoint locations at aircraft altitude at which the voids in the point clouds could theoretically be imaged. This work is based on the assumption that inclusion of more images of the void areas in the 3D reconstruction process will reduce the number of voids in the point cloud that were a result of lack of coverage. Voids resulting from texturally difficult areas will not benefit from more imagery in the reconstruction process, and thus are identified and removed prior to the determination of future potential imaging locations

Automated identification of voids in three-dimensional point clouds

In the construction of three-dimensional (3D) point clouds from multi-view aerial imagery, voids in the point cloud often exist where multiple views of the area were not obtained during collection. A method is presented for identifying these voids. In this work, point clouds are derived from oblique aerial imagery using multi-view techniques from the photogrammetry and computer vision communities. A voxel-based approach is used to partition the 3D space and each voxel is classified as containing or not containing derived points. Using the imagery and the position of the camera, it is possible to analyze what the cameras can and cannot see, thereby making it possible to label the voxels as occupied, free, and non-classified spaces. Voids in the data will manifest themselves in the non-classified voxels. This method has been tested on high-frame-rate oblique aerial imagery captured over Rochester, NY as well as synthetic data sets. Also presented is a unique synthetic dataset for 3D reconstruction. The data set, created with the Rochester Institute of Technology’s Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, provides high-fidelity radiometric data in addition to known 3D locations and surface normals for each pixel location in an image scene. This data set is available to the community for use in their related research

Radiomics and prostate MRI: Current role and future applications

Multiparametric prostate magnetic resonance imaging (mpMRI) is widely used as a triage test for men at a risk of prostate cancer. However, the traditional role of mpMRI was confined to prostate cancer staging. Radiomics is the quantitative extraction and analysis of minable data from medical images; it is emerging as a promising tool to detect and categorize prostate lesions. In this paper we review the role of radiomics applied to prostate mpMRI in detection and localization of prostate cancer, prediction of Gleason score and PI-RADS classification, prediction of extracapsular extension and of biochemical recurrence. We also provide a future perspective of artificial intelligence (machine learning and deep learning) applied to the field of prostate cancer

Deep learning-based methods for prostate segmentation in magnetic resonance imaging

Magnetic Resonance Imaging-based prostate segmentation is an essential task for adaptive radiotherapy and for radiomics studies whose purpose is to identify associations between imaging features and patient outcomes. Because manual delineation is a time-consuming task, we present three deep-learning (DL) approaches, namely UNet, efficient neural network (ENet), and efficient residual factorized convNet (ERFNet), whose aim is to tackle the fully-automated, real-time, and 3D delineation process of the prostate gland on T2-weighted MRI. While UNet is used in many biomedical image delineation applications, ENet and ERFNet are mainly applied in self-driving cars to compensate for limited hardware availability while still achieving accurate segmentation. We apply these models to a limited set of 85 manual prostate segmentations using the k-fold validation strategy and the Tversky loss function and we compare their results. We find that ENet and UNet are more accurate than ERFNet, with ENet much faster than UNet. Specifically, ENet obtains a dice similarity coefficient of 90.89% and a segmentation time of about 6 s using central processing unit (CPU) hardware to simulate real clinical conditions where graphics processing unit (GPU) is not always available. In conclusion, ENet could be efficiently applied for prostate delineation even in small image training datasets with potential benefit for patient management personalization

Lightcurve analysis and rotation period of 6372 Walker

6372 Walker is a main-belt asteroid discovered in 1985 by C.S. Shoemaker at Palomar Observatory and was last observed in May of 2018 (JPL, 2019). It has a diameter of 42.13 km and orbital period of 5.68 yr.peer-reviewe

Homogeneously derived transit timings for 17 exoplanets and reassessed TTV trends for WASP-12 and WASP-4

We homogeneously analyse ∼3.2 × 105 photometric measurements for ∼1100 transit lightcurves belonging to 17 exoplanet hosts. The photometric data cover 16 years 2004–2019 and include amateur and professional observations. Old archival lightcurves were reprocessed using up-to-date exoplanetary parameters and empirically debiased limb-darkening models. We also derive self-consistent transit and radial-velocity fits for 13 targets. We confirm the nonlinear TTV trend in the WASP-12 data at a high significance, and with a consistent magnitude. However, Doppler data reveal hints of a radial acceleration about ( − 7.5 ± 2.2) m/s/yr, indicating the presence of unseen distant companions, and suggesting that roughly 10 per cent of the observed TTV was induced via the light-travel (or Roemer) effect. For WASP-4, a similar TTV trend suspected after the recent TESS observations appears controversial and model-dependent. It is not supported by our homogeneus TTV sample, including 10 ground-based EXPANSION lightcurves obtained in 2018 simultaneously with TESS. Even if the TTV trend itself does exist in WASP-4, its magnitude and tidal nature are uncertain. Doppler data cannot entirely rule out the Roemer effect induced by possible distant companions

A search for the afterglows, kilonovae, and host galaxies of two short GRBs: GRB 211106A and GRB 211227A

Context: GRB 211106A and GRB 211227A are recent gamma-ray bursts (GRBs) with initial X-ray positions suggesting associations with nearby galaxies (z < 0.7). Their prompt emission characteristics indicate GRB 211106A is a short-duration GRB and GRB 211227A is a short GRB with extended emission, likely originating from compact binary mergers. However, classifying solely based on prompt emission can be misleading. Aims: These short GRBs in the local Universe offer opportunities to search for associated kilonova (KN) emission and study host galaxy properties in detail. Methods: We conducted deep optical and NIR follow-up using ESO-VLT FORS2, HAWK-I, and MUSE for GRB 211106A, and ESO-VLT FORS2 and X-Shooter for GRB 211227A, starting shortly after the X-ray afterglow detection. We performed photometric analysis to look for afterglow and KN emissions associated with the bursts, along with host galaxy imaging and spectroscopy. Optical/NIR results were compared with Swift X-Ray Telescope (XRT) and other high-energy data. Results: For both GRBs we placed deep limits to the optical/NIR afterglow and KN emission. Host galaxies were identified: GRB 211106A at photometric z = 0.64 and GRB 211227A at spectroscopic z = 0.228. Host galaxy properties aligned with typical short GRB hosts. We also compared the properties of the bursts with the S-BAT4 sample to further examined the nature of these events. Conclusions: Study of prompt and afterglow phases, along with host galaxy analysis, confirms GRB 211106A as a short GRB and GRB 211227A as a short GRB with extended emission. The absence of optical/NIR counterparts is likely due to local extinction for GRB 211106A and a faint kilonova for GRB 211227A.Comment: Accepted to A&A on 08 August 2023, 21 pages, 24 figure

Observational study on efficacy of negative expiratory pressure test proposed as screening for obstructive sleep apnea syndrome among commercial interstate bus drivers - protocol study

<p>Abstract</p> <p>Background</p> <p>Obstructive sleep apnea (OSA) is a respiratory disease characterized by the collapse of the extrathoracic airway and has important social implications related to accidents and cardiovascular risk. The main objective of the present study was to investigate whether the drop in expiratory flow and the volume expired in 0.2 s during the application of negative expiratory pressure (NEP) are associated with the presence and severity of OSA in a population of professional interstate bus drivers who travel medium and long distances.</p> <p>Methods/Design</p> <p>An observational, analytic study will be carried out involving adult male subjects of an interstate bus company. Those who agree to participate will undergo a detailed patient history, physical examination involving determination of blood pressure, anthropometric data, circumference measurements (hips, waist and neck), tonsils and Mallampati index. Moreover, specific questionnaires addressing sleep apnea and excessive daytime sleepiness will be administered. Data acquisition will be completely anonymous. Following the medical examination, the participants will perform a spirometry, NEP test and standard overnight polysomnography. The NEP test is performed through the administration of negative pressure at the mouth during expiration. This is a practical test performed while awake and requires little cooperation from the subject. In the absence of expiratory flow limitation, the increase in the pressure gradient between the alveoli and open upper airway caused by NEP results in an increase in expiratory flow.</p> <p>Discussion</p> <p>Despite the abundance of scientific evidence, OSA is still underdiagnosed in the general population. In addition, diagnostic procedures are expensive, and predictive criteria are still unsatisfactory. Because increased upper airway collapsibility is one of the main determinants of OSA, the response to the application of NEP could be a predictor of this disorder. With the enrollment of this study protocol, the expectation is to encounter predictive NEP values for different degrees of OSA in order to contribute toward an early diagnosis of this condition and reduce its impact and complications among commercial interstate bus drivers.</p> <p>Trial registration</p> <p><it>Registro Brasileiro de Ensaios Clinicos </it>(local acronym RBEC) [Internet]: Rio de Janeiro (RJ): <it>Instituto de Informaçao Cientifica e Tecnologica em Saude </it>(Brazil); 2010 - Identifier RBR-7dq5xx. Cross-sectional study on efficacy of negative expiratory pressure test proposed as screening for obstructive sleep apnea syndrome among commercial interstate bus drivers; 2011 May 31 [7 pages]. Available from <url>http://www.ensaiosclinicos.gov.br/rg/RBR-7dq5xx/</url>.</p

Discovery of a young low-mass brown dwarf transiting a fast-rotating F-type star by the Galactic Plane eXoplanet (GPX) survey

We announce the discovery of GPX-1 b, a transiting brown dwarf with a mass of $19.7\pm 1.6$ $M_{\mathrm{Jup}}$ and a radius of $1.47\pm0.10$ $R_{\mathrm{Jup}}$, the first sub-stellar object discovered by the Galactic Plane eXoplanet (GPX) survey. The brown dwarf transits a moderately bright ($V$ = 12.3 mag) fast-rotating F-type star with a projected rotational velocity $v\sin{ i_*}=40\pm10$ km/s. We use the isochrone placement algorithm to characterize the host star, which has effective temperature $7000\pm200$ K, mass $1.68\pm0.10$ $M_{\mathrm{Sun}}$, radius $1.56\pm0.10$ $R_{\mathrm{Sun}}$ and approximate age $0.27_{-0.15}^{+0.09}$ Gyr. GPX-1 b has an orbital period of $\sim$1.75 d, and a transit depth of $0.90\pm0.03$ %. We describe the GPX transit detection observations, subsequent photometric and speckle-interferometric follow-up observations, and SOPHIE spectroscopic measurements, which allowed us to establish the presence of a sub-stellar object around the host star. GPX-1 was observed at 30-min integrations by TESS in Sector 18, but the data is affected by blending with a 3.4 mag brighter star 42 arcsec away. GPX-1 b is one of about two dozen transiting brown dwarfs known to date, with a mass close to the theoretical brown dwarf/gas giant planet mass transition boundary. Since GPX-1 is a moderately bright and fast-rotating star, it can be followed-up by the means of Doppler tomography.Comment: 13 pages, 13 figures, accepted to MNRAS in May 202

ExoClock Project III: 450 new exoplanet ephemerides from ground and space observations

The ExoClock project has been created with the aim of increasing the efficiency of the Ariel mission. It will achieve this by continuously monitoring and updating the ephemerides of Ariel candidates over an extended period, in order to produce a consistent catalogue of reliable and precise ephemerides. This work presents a homogenous catalogue of updated ephemerides for 450 planets, generated by the integration of $\sim$18000 data points from multiple sources. These sources include observations from ground-based telescopes (ExoClock network and ETD), mid-time values from the literature and light-curves from space telescopes (Kepler/K2 and TESS). With all the above, we manage to collect observations for half of the post-discovery years (median), with data that have a median uncertainty less than one minute. In comparison with literature, the ephemerides generated by the project are more precise and less biased. More than 40\% of the initial literature ephemerides had to be updated to reach the goals of the project, as they were either of low precision or drifting. Moreover, the integrated approach of the project enables both the monitoring of the majority of the Ariel candidates (95\%), and also the identification of missing data. The dedicated ExoClock network effectively supports this task by contributing additional observations when a gap in the data is identified. These results highlight the need for continuous monitoring to increase the observing coverage of the candidate planets. Finally, the extended observing coverage of planets allows us to detect trends (TTVs - Transit Timing Variations) for a sample of 19 planets. All products, data, and codes used in this work are open and accessible to the wider scientific community.Comment: Recommended for publication to ApJS (reviewer's comments implemented). Main body: 13 pages, total: 77 pages, 7 figures, 7 tables. Data available at http://doi.org/10.17605/OSF.IO/P298