Perceptual Aliasing is one of the main problems in simultaneous localization and mapping (SLAM). Wrong associations between different places may lead to failure of the whole map. Research on ...structure information is rarely investigated among existing solutions to this problem. In cases of visual SLAM without sensors, such as LiDAR or Inertial Measurement Unit (IMU), structure information can rarely be obtained due to the sparsity of 3D points, which also makes structure analysis complex. This study provides a spherical harmonics (SH) based fast structural representation (SH-FS) in visual SLAM using sparse point clouds, which extracts the structure information from sparse points into single vector. SH-FS was applied in conventional feature-based loop closing process. Furthermore, a structure-aware loop closing method in visual SLAM was proposed to improve the robustness of SLAM systems. Moreover, our methods show a favorable performance in extensive experiments on different large-scale real world datasets.
In this letter, we present a method for estimating a dense depth map from a sparse LIDAR point cloud and an image sequence. Our proposed method relies on a directionally biased propagation of known ...depth to missing areas based on semantic segmentation. Additionally, we classify different object boundaries as either occluded or connected to limit the extent of the data propagation. At the regions with large missing point cloud data, we depend on estimated depth using motion stereo. We embed our method on a bounded interpolation strategy which also considers pixel distance, depth difference and color gradient. We then perform an optimization step based on tensor-based TGV-L2 denoising. Our results show that directional propagation and semantic boundary classification can improve the accuracy of interpolation along the edges for different types of objects. Moreover, our motion stereo scheme increases the reliability of extrapolated depth at the regions with large missing point cloud data. Finally, we show that our implementation strategy can achieve reliable results in real time.
We propose a non-learning depth completion method for a sparse depth map captured using a light detection and ranging (LiDAR) sensor guided by a pair of stereo images. Generally, conventional ...stereo-aided depth completion methods have two limiations. (i) they assume the given sparse depth map is accurately aligned to the input image, whereas the alignment is difficult to achieve in practice; (ii) they have limited accuracy in the long range because the depth is estimated by pixel disparity. To solve the abovementioned limitations, we propose selective stereo matching (SSM) that searches the most appropriate depth value for each image pixel from its neighborly projected LiDAR points based on an energy minimization framework. This depth selection approach can handle any type of mis-projection. Moreover, SSM has an advantage in terms of long-range depth accuracy because it directly uses the LiDAR measurement rather than the depth acquired from the stereo. SSM is a discrete process; thus, we apply variational smoothing with binary anisotropic diffusion tensor (B-ADT) to generate a continuous depth map while preserving depth discontinuity across object boundaries. Experimentally, compared with the previous state-of-the-art stereo-aided depth completion, the proposed method reduced the mean absolute error (MAE) of the depth estimation to 0.65 times and demonstrated approximately twice more accurate estimation in the long range. Moreover, under various LiDAR-camera calibration errors, the proposed method reduced the depth estimation MAE to 0.34-0.93 times from previous depth completion methods.
Bronchial thermoplasty (BT) is effective in some severe asthma patients; however, the specific asthma phenotypes that produce a good response to BT are not fully understood. Clinical data were ...retrospectively reviewed in severe asthma patients who underwent BT at a single institution in Japan. At the follow-up assessment, the Asthma Quality of Life Questionnaire (AQLQ) scores (P = 0.003), maintenance oral corticosteroid doses (P = 0.027), and exacerbation frequency (P = 0.017) were significantly improved, while prebronchodilator-forced expiratory volume in 1 second (% predicted) did not significantly change (P = 0.19). When we grouped the patients into 2 groups according to their body mass index levels, the AQLQ scores were more improved in patients with overweight/obesity than those with normal weight (P = 0.01). This study showed that patients with non-controlled severe asthma exhibiting overweight/obesity and low quality of life had potential benefits from BT.
In this paper, we propose a dynamic calibration between a mobile robot and a device using simultaneous localization and mapping (SLAM) technology, which we termed as the SLAM device, for a robot ...navigation system. The navigation framework assumes loose mounting of SLAM device for easy use and requires an online adjustment to remove localization errors. The online adjustment method dynamically corrects not only the calibration errors between the SLAM device and the part of the robot to which the device is attached but also the robot encoder errors by calibrating the whole body of the robot. The online adjustment assumes that the information of the external environment and shape information of the robot are consistent. In addition to the online adjustment, we also present an offline calibration between a robot and device. The offline calibration is motion-based and we clarify the most efficient method based on the number of degrees-of-freedom of the robot movement. Our method can be easily used for various types of robots with sufficiently precise localization for navigation. In the experiments, we confirm the parameters obtained via two types of offline calibration based on the degree of freedom of robot movement. We also validate the effectiveness of the online adjustment method by plotting localized position errors during a robots intense movement. Finally, we demonstrate the navigation using a SLAM device.
Interstitial lung disease (ILD) has rarely been reported as a manifestation of giant cell arteritis (GCA). We herein report a unique case of GCA in a 76-year-old woman who presented with ILD as an ...initial manifestation of GCA. Ten years before admission, she had been diagnosed with granulomatous ILD of unknown etiology. Corticosteroid therapy induced remission. One year after the cessation of corticosteroid therapy, she was admitted with a persistent fever. After admission, she developed left oculomotor paralysis. Positron emission tomography with 2-deoxy-2-fluorine-18fluoro-D-glucose integrated with computed tomography (18F-FDG PET/CT) proved extremely useful in establishing the diagnosis. Our case promotes awareness of GCA as a possible diagnosis for granulomatous ILD with unknown etiology.
Accidental falls among inpatients are a substantial cause of hospital injury. A number of successful experimental studies on fall prevention have shown the importance and efficacy of multifactorial ...intervention, though success rates vary. However, the importance of staff compliance with these effective, but often time-consuming, multifactorial interventions has not been fully investigated in a routine clinical setting. The purpose of this observational study was to describe the effectiveness of a multidisciplinary quality improvement (QI) activity for accidental fall prevention, with particular focus on staff compliance in a non-experimental clinical setting.
This observational study was conducted from July 2004 through December 2010 at St. Luke's International Hospital in Tokyo, Japan. The QI activity for in-patient falls prevention consisted of: 1) the fall risk assessment tool, 2) an intervention protocol to prevent in-patient falls, 3) specific environmental safety interventions, 4) staff education, and 5) multidisciplinary healthcare staff compliance monitoring and feedback mechanisms.
The overall fall rate was 2.13 falls per 1000 patient days (350/164331) in 2004 versus 1.53 falls per 1000 patient days (263/172325) in 2010, representing a significant decrease (p = 0.039). In the first 6 months, compliance with use of the falling risk assessment tool at admission was 91.5% in 2007 (3998/4368), increasing to 97.6% in 2010 (10564/10828). The staff compliance rate of implementing an appropriate intervention plan was 85.9% in 2007, increasing to 95.3% in 2010.
In our study we observed a substantial decrease in patient fall rates and an increase of staff compliance with a newly implemented falls prevention program. A systematized QI approach that closely involves, encourages, and educates healthcare staff at multiple levels is effective.
This paper proposes a targetless and automatic camera-LiDAR calibration method. Our approach extends the hand-eye calibration framework to 2D-3D calibration. The scaled camera motions are accurately ...calculated using a sensor-fusion odometry method. We also clarify the suitable motions for our calibration method. Whereas other calibrations require the LiDAR reflectance data and an initial extrinsic parameter, the proposed method requires only the three-dimensional point cloud and the camera image. The effectiveness of the method is demonstrated in experiments using several sensor configurations in indoor and outdoor scenes. Our method achieved higher accuracy than comparable state-of-the-art methods.
Immune checkpoint inhibitors (ICIs) have been used to treat lung cancer. Several types of ICI-related interstitial lung diseases have been reported, including organizing pneumonia, non-specific ...interstitial pneumonia, and diffuse alveolar damage. However, pembrolizumab-associated bronchiolitis requiring treatment for persistent cough has not yet been reported. Here, we describe a patient who developed dry cough while being treated with pembrolizumab for lung adenocarcinoma. Radiography and lung biopsy findings indicated bronchiolitis. His cough improved after the discontinuation of pembrolizumab and treatment with erythromycin, an inhaled corticosteroid, a long-acting muscarinic antagonist, and a long-acting β2 agonist.
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