scholarly journals Respiration Monitoring for Premature Neonates in NICU

2019 ◽  
Vol 9 (23) ◽  
pp. 5246
Author(s):  
Yue Sun ◽  
Wenjin Wang ◽  
Xi Long ◽  
Mohammed Meftah ◽  
Tao Tan ◽  
...  
Keyword(s):  
Optical Flow ◽  
Premature Infants ◽  
Neonatal Intensive Care ◽  
Correlation Coefficients ◽  
Estimation Methods ◽  
Neonatal Intensive Care Units ◽  
Monitoring Method ◽  
Respiration Monitoring ◽  
Flow Estimation ◽  
Video Frames

In this paper, we investigate an automated pipeline to estimate respiration signals from videos for premature infants in neonatal intensive care units (NICUs). Two flow estimation methods, namely the conventional optical flow- and deep learning-based flow estimation methods, were employed and compared to estimate pixel motion vectors between adjacent video frames. The respiratory signal is further extracted via motion factorization. The proposed methods were evaluated by comparing our automated extracted respiration signals to that extracted from chest impedance on videos of five premature infants. The overall average cross-correlation coefficients are 0.70 for the optical flow-based method and 0.74 for the deep flow-based method. The average root mean-squared errors are 6.10 and 4.55 for the optical flow- and the deep flow-based methods, respectively. The experimental results are promising for further investigation and clinical application of the video-based respiration monitoring method for infants in NICUs.

Improved optical flow estimation methods using Atomic Functions

2012 ◽  
Author(s):  
Martha Cejudo-Torres ◽  
Enrique Escamilla-Hernandez ◽  
Mariko Nakano-Miyatake ◽  
Hector Perez Meana
Keyword(s):  
Optical Flow ◽  
Estimation Methods ◽  
Flow Estimation ◽  
Optical Flow Estimation

scholarly journals Ghost-removal image warping for optical flow estimation

2019 ◽  
Vol 277 ◽  
pp. 02002
Author(s):  
Song Wang ◽  
Zengfu Wang
Keyword(s):  
Optical Flow ◽  
Image Warping ◽  
Estimation Methods ◽  
Flow Estimation ◽  
Optical Flow Estimation ◽  
Flow Information ◽  
Ghosting Artifacts ◽  
Compensation Technique ◽  
Image Compensation ◽  
Traditional Image

Traditional image warping methods used in optical flow estimation usually adopt simple interpolation strategies to obtain the warped images. But without considering the characteristic of occluded regions, the traditional methods may result in undesirable ghosting artifacts. To tackle this problem, in this paper we propose a novel image warping method to effectively remove ghosting artifacts. To be Specific, when given a warped image, the ghost regions are firstly discriminated using the optical flow information. Then, we use a new image compensation technique to eliminate the ghosting artifacts. The proposed method can avoid serious distortion in the warped images, therefore can prevent error propagation in the coarse-to-fine optical flow estimation schemes. Meanwhile, our approach can be easily integrated into various optical flow estimation methods. Experimental results on some popular datasets such as Flying Chairs and MPI-Sintel demonstrate that the proposed method can improve the performance of current optical flow estimation methods.

scholarly journals Optical Flow Estimation with Occlusion Detection

Algorithms ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 92
Author(s):  
Song Wang ◽  
Zengfu Wang
Keyword(s):  
Optical Flow ◽  
Feature Matching ◽  
Estimation Algorithm ◽  
Occlusion Detection ◽  
Multiple Sources ◽  
Flow Estimation ◽  
Optical Flow Estimation ◽  
Dense Optical Flow ◽  
Video Frames ◽  
Optimization Function

The dense optical flow estimation under occlusion is a challenging task. Occlusion may result in ambiguity in optical flow estimation, while accurate occlusion detection can reduce the error. In this paper, we propose a robust optical flow estimation algorithm with reliable occlusion detection. Firstly, the occlusion areas in successive video frames are detected by integrating various information from multiple sources including feature matching, motion edges, warped images and occlusion consistency. Then optimization function with occlusion coefficient and selective region smoothing are used to obtain the optical flow estimation of the non-occlusion areas and occlusion areas respectively. Experimental results show that the algorithm proposed in this paper is an effective algorithm for dense optical flow estimation.

Drug Utilization in Very Premature Infants in Neonatal Intensive Care Units

1991 ◽  
Vol 17 (3-4) ◽  
pp. 167-171 ◽  
Author(s):  
L. Gortner ◽  
U. Bernsau ◽  
M. Brand ◽  
H.H. Hellwege ◽  
G. Hieronimie ◽  
...  
Keyword(s):  
Intensive Care ◽  
Intensive Care Units ◽  
Drug Utilization ◽  
Premature Infants ◽  
Neonatal Intensive Care ◽  
Neonatal Intensive Care Units ◽  
Very Premature Infants

National Institues of Health Recommends the Routine Use of H2 Blockers in Preterm Infants be Carefully Evaluated

2006 ◽  
Vol 25 (3) ◽  
pp. 223-224 ◽  
Author(s):  
Elizabeth Pulsifer-Anderson ◽  
Ronnie Guillet
Keyword(s):  
Intensive Care ◽  
Preterm Infants ◽  
Premature Infants ◽  
Neonatal Intensive Care ◽  
Current Practice ◽  
Acid Reflux ◽  
National Institutes Of Health ◽  
Neonatal Intensive Care Units ◽  
New Findings ◽  
The U.S

ARETROSPECTIVE ANALYSIS OF data from 11,000 preterm infants in neonatal intensive care units (NICUs) in the U.S. found that infants receiving H2 blockers such as Zantac, Tagamet, Pepcid, and Axid were more likely to develop necrotizing enterocolitis (NEC).1 The study was funded by the National Institutes of Health (NIH). As a result of the findings of this study, Elias A. Zerhouni, MD, Director of the National Institutes of Health, issued a press release in February, 2006, stating, “This study strongly suggests that the current practice of prescribing H2 blockers to prevent or treat acid reflux in premature infants needs to be carefully reevaluated by all concerned in light of these new findings.”2

scholarly journals Neonatal Anemia

2021 ◽  
Author(s):  
Laura M. Dionisio ◽  
Thamires A. Dzirba
Keyword(s):  
Intensive Care ◽  
Clinical Practice ◽  
Iron Deficiency ◽  
Blood Loss ◽  
Blood Cell ◽  
Preterm Infants ◽  
Premature Infants ◽  
Neonatal Intensive Care ◽  
Laboratory Tests ◽  
Neonatal Intensive Care Units

Neonatal anemia and iron deficiency are frequent founds in neonatal intensive care units (NICUs). The three major causes of anemia in neonates are blood loss, reduced red blood cell production, and increased degradation of the erythrocytes. Premature infants in ICUs have high levels of iron deficiency, and ascertaining the cause of anemia in this group of patients can be a challenge in clinical practice. This chapter provides an updated review of neonatal anemia. It will concern the pathophysiology of neonatal anemia in term and preterm infants and a detailed discussion of the traditional and innovative laboratory tests for diagnosis and assessment of this condition in the ICUs

scholarly journals MOUNTAINOUS REMOTE SENSING IMAGES REGISTRATION BASED ON IMPROVED OPTICAL FLOW ESTIMATION

2019 ◽  
Vol IV-2/W5 ◽  
pp. 479-484 ◽  
Author(s):  
R. Feng ◽  
X. Li ◽  
H. Shen
Keyword(s):  
Remote Sensing ◽  
Optical Flow ◽  
Remote Sensing Image ◽  
Transformation Model ◽  
Geometric Distortion ◽  
Estimation Methods ◽  
Remote Sensing Images ◽  
Flow Estimation ◽  
Optical Flow Estimation ◽  
Feature Based

<p><strong>Abstract.</strong> Mountainous remote sensing images registration is more complicated than in other areas as geometric distortion caused by topographic relief, which could not be precisely achieved via constructing local mapping functions in the feature-based framework. Optical flow algorithm estimating motion of consecutive frames in computer vision pixel by pixel is introduced for mountainous remote sensing images registration. However, it is sensitive to land cover changes that are inevitable for remote sensing image, resulting in incorrect displacement. To address this problem, we proposed an improved optical flow estimation concentrated on post-processing, namely displacement modification. First of all, the Laplacian of Gaussian (LoG) algorithm is employed to detect the abnormal value in color map of displacement. Then, the abnormal displacement is recalculated in the interpolation surface constructed by the rest accurate displacements. Following the successful coordinate transformation and resampling, the registration outcome is generated. Experiments demonstrated that the proposed method is insensitive in changeable region of mountainous remote sensing image, generating precise registration, outperforming the other local transformation model estimation methods in both visual judgment and quantitative evaluation.</p>

scholarly journals Motion Vector Field Estimation Using Brightness Constancy Assumption and Epipolar Geometry Constraint

2014 ◽  
Vol II-1 ◽  
pp. 9-16 ◽  
Author(s):  
S. Hosseinyalamdary ◽  
A. Yilmaz
Keyword(s):  
Vector Field ◽  
Optical Flow ◽  
Motion Vector ◽  
Epipolar Geometry ◽  
Estimation Methods ◽  
Brightness Constancy ◽  
Flow Estimation ◽  
Optical Flow Estimation ◽  
Motion Vector Field ◽  
Field Estimation

In most Photogrammetry and computer vision tasks, finding the corresponding points among images is required. Among many, the Lucas-Kanade optical flow estimation has been employed for tracking interest points as well as motion vector field estimation. This paper uses the IMU measurements to reconstruct the epipolar geometry and it integrates the epipolar geometry constraint with the brightness constancy assumption in the Lucas-Kanade method. The proposed method has been tested using the KITTI dataset. The results show the improvement in motion vector field estimation in comparison to the Lucas-Kanade optical flow estimation. The same approach has been used in the KLT tracker and it has been shown that using epipolar geometry constraint can improve the KLT tracker. It is recommended that the epipolar geometry constraint is used in advanced variational optical flow estimation methods.

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