scholarly journals A Multi-Channel Uncertainty-Aware Multi-Resolution Network for MR to CT Synthesis

2021 ◽  
Vol 11 (4) ◽  
pp. 1667
Author(s):  
Kerstin Klaser ◽  
Pedro Borges ◽  
Richard Shaw ◽  
Marta Ranzini ◽  
Marc Modat ◽  
...  
Keyword(s):  
Medical Image Analysis ◽  
Absolute Error ◽  
Magnetic Resonance Images ◽  
The Body ◽  
Whole Body ◽  
Image Size ◽  
Body Images ◽  
Image Translation ◽  
The Mean ◽  
Synthetic Ct

Synthesising computed tomography (CT) images from magnetic resonance images (MRI) plays an important role in the field of medical image analysis, both for quantification and diagnostic purposes. Convolutional neural networks (CNNs) have achieved state-of-the-art results in image-to-image translation for brain applications. However, synthesising whole-body images remains largely uncharted territory, involving many challenges, including large image size and limited field of view, complex spatial context, and anatomical differences between images acquired at different times. We propose the use of an uncertainty-aware multi-channel multi-resolution 3D cascade network specifically aiming for whole-body MR to CT synthesis. The Mean Absolute Error on the synthetic CT generated with the MultiResunc network (73.90 HU) is compared to multiple baseline CNNs like 3D U-Net (92.89 HU), HighRes3DNet (89.05 HU) and deep boosted regression (77.58 HU) and shows superior synthesis performance. We ultimately exploit the extrapolation properties of the MultiRes networks on sub-regions of the body.

scholarly journals Estimation of Motion and Respiratory Characteristics during the Meditation Practice Based on Video Analysis

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3771
Author(s):  
Alexey Kashevnik ◽  
Walaa Othman ◽  
Igor Ryabchikov ◽  
Nikolay Shilov
Keyword(s):  
Respiratory Rate ◽  
Evaluation System ◽  
Body Movement ◽  
Absolute Error ◽  
The Body ◽  
Meditation Practice ◽  
Body Parts ◽  
Mental Health Training ◽  
Negative Thoughts ◽  
The Mean

Meditation practice is mental health training. It helps people to reduce stress and suppress negative thoughts. In this paper, we propose a camera-based meditation evaluation system, that helps meditators to improve their performance. We rely on two main criteria to measure the focus: the breathing characteristics (respiratory rate, breathing rhythmicity and stability), and the body movement. We introduce a contactless sensor to measure the respiratory rate based on a smartphone camera by detecting the chest keypoint at each frame, using an optical flow based algorithm to calculate the displacement between frames, filtering and de-noising the chest movement signal, and calculating the number of real peaks in this signal. We also present an approach to detecting the movement of different body parts (head, thorax, shoulders, elbows, wrists, stomach and knees). We have collected a non-annotated dataset for meditation practice videos consists of ninety videos and the annotated dataset consists of eight videos. The non-annotated dataset was categorized into beginner and professional meditators and was used for the development of the algorithm and for tuning the parameters. The annotated dataset was used for evaluation and showed that human activity during meditation practice could be correctly estimated by the presented approach and that the mean absolute error for the respiratory rate is around 1.75 BPM, which can be considered tolerable for the meditation application.

scholarly journals Structural Organization of the Optic Lobe of Grey Breasted Helmeted Guinea Fowl (*Numida meleagris galeata*) at Pre-Hatch Study

2016 ◽  
Vol 7 (2) ◽  
pp. 26
Author(s):  
Wanmi Nathaniel ◽  
Onyeanusi I. Barth ◽  
Nzalak J. Oliver ◽  
Aluwong Tanang
Keyword(s):  
Body Weight ◽  
Structural Organization ◽  
Optic Lobe ◽  
Guinea Fowl ◽  
The Body ◽  
Whole Body ◽  
Steady Increase ◽  
Numida Meleagris ◽  
The Mean ◽  
Immature Cells

<p class="jbls-body"><span lang="EN-GB">A total of one hundred and seventy-three fertilized eggs were used for morphometry, gross and histological studies. At day 4 of incubation, the mean body weight of the helmeted guinea fowl embryo was 0.6401 ± 0.0211 g. It was at day 10 of incubation that there was an increase in the whole body weight of the embryo to be 0.8650 ± 0.676 g. The whole brain weight indicated relative increased at day 4 as compared to that of the whole body weight. Graphically, there were steady increase in the body, brain and optic lobe weights. Histologically, cells and neurones that make up the optic lobe is probably as a result of the migration of immature cells from the ventricular neuroepithelium. </span></p>

Spect imaging of the serotonin transporter using a novel ligand - 123-I mZIENT - in human subjects - a dosimetry and biodisortribution study

2011 ◽  
Vol 26 (S2) ◽  
pp. 935-935
Author(s):  
R. Krishnadas ◽  
A. Nicol ◽  
S. Champion ◽  
S. Pimlott ◽  
J. Stehouwer ◽  
...  
Keyword(s):  
Healthy Volunteers ◽  
Gamma Camera ◽  
Human Subjects ◽  
The Body ◽  
Whole Body ◽  
Body Images ◽  
Promising Agent ◽  
Regional Brain ◽  
The Brain ◽  
Spect Images

Levels of serotonin in the body are regulated by the serotonin transporters (SERT), which are predominantly located on the presynaptic terminals of serotonin-containing neurons. Alterations in the density of SERT have been implicated in the pathophysiology of many neuropsychiatric disorders.AimTo evaluate 123-I mZIENT (2(S)-[(S)-2b-carbomethoxy-3b-[3′-((Z)-2-iodoethenyl)phenyl]nortropane), a novel radiopharmaceutical for imaging SERT. The bio-distribution of the radiopharmaceutical in humans was investigated and dosimetry performed.MethodsThe study includes three healthy volunteers and three patients receiving SSRIs. Whole body images obtained on a gamma camera at 10 minutes, 1, 2, 3, 6, 24 and 48 hours post administration. Dosimetry was performed. ROIs were drawn over the brain, heart, kidneys, liver, lungs, salivary glands, spleen, thyroid and intestines. Blood was sampled at 5, 15, & 30 minutes and 1, 2, 3, 6, 24 and 48 hours post administration. Urine was collected at 1, 2, 3, 4, 6, 24 and 48 hours. Brain SPECT images were obtained using a neuroSPECT scanner at 4 hours, evaluated visually and analysed using ROI analysis.ResultsHigh quality SPECT images can be obtained after 100–150 MBq 123-ImZEINT. Regional brain uptake was observed in midbrain and basal ganglia in healthy volunteers, consistent with the known distribution of SERT. Biodistribution images demonstrated highest uptake in the lungs, brain, liver and intestines. The effective dose was within range of other commonly used ligands and is acceptable for clinical imaging.Conclusion123-ImZIENT is a promising agent for imaging SERT in humans with acceptable dosimetry.

Enhancement of Tumor Contrast on Radioimmunoscans by Using Mixtures of Monoclonal Antibody F(ab’)2 Fragments

1986 ◽  
Vol 25 (06) ◽  
pp. 216-219 ◽  
Author(s):  
A. Alavi ◽  
H. Koprowski ◽  
D. Herlyn ◽  
D. L. Munz
Keyword(s):  
Monoclonal Antibody ◽  
Gastrointestinal Tract ◽  
Nude Mice ◽  
Half Life ◽  
The Body ◽  
Whole Body ◽  
Antigenic Determinants ◽  
Body Images ◽  
Biological Half Life ◽  
Adenocarcinoma Cells

F(ab’)2 fragments of MAbs GA 73-3 (IgG 2a) and CO 29.11 (IgG 1), which detect distinct antigenic determinants on adenocarcinoma cells of the gastrointestinal tract, were labeled with 131I using the iodogen method. 41 nude mice bearing SW-948 CRC tumors were injected either with a mixture of 100 ¼Ci (11 ¼g) each (n = 9) of the two 131l-F(ab’)2 fragments or with either fragment alone at various doses (each group consisting of 8 mice): GA 73-3,100 ¼Ci (11 ¼g) and 200 ¼Ci (25 ¼g); CO 29.11,100 ¼Ci (11 ¼g) and 200 ¼Ci (26 ¼g). Whole-body images of the mice were obtained daily for up to six days after injection. Ratios of cpm/pixel in the tumor to those in the rest of the body (rob), representing tumor contrast, were significantly (p <0.05) higher in the group of mice injected with the mixture (3.9 ± 1.5) as compared to those given 100 or 200 jiCi of either fragment separately. The biological half-life (T1/2 biol) of the mixture (44.7 ± 14.5 h) in the CRC tumors was significantly (p <0.05) longer than T1/2 biol determined in the groups given either fragment alone. Tv bioL in the rob was similar in all groups of mice examined.

scholarly journals An Image-Based Approach to Obtaining Anthropometric Measurements for Inertia Modeling

2009 ◽  
Vol 25 (3) ◽  
pp. 265-270 ◽  
Author(s):  
Marianne J. R. Gittoes ◽  
Ian N. Bezodis ◽  
Cassie Wilson
Keyword(s):  
Absolute Error ◽  
Anthropometric Measurements ◽  
Whole Body ◽  
Parameter Determination ◽  
Body Images ◽  
Still Images ◽  
Improve Model ◽  
Subject Specific ◽  
Inertia Model ◽  
Data Collections

This study aimed to develop and evaluate an image-based method of obtaining anthropometric measurements for accurate subject-specific inertia parameter determination using Yeadon’s (1990) inertia model. Ninety-five anthropometric measurements were obtained directly from five athletic performers and indirectly from digitization of subject-specific whole-body still images. The direct and image-based measurements were used as input into Yeadon’s (1990) inertia model. The overall absolute error in predicted whole-body mass achieved using the image-based approach (2.87%) compared well to that achieved using the direct measurements (2.10%). The inclusion of image-based anthropometric measurements obtained from extremity (hand and feet) images was not found to consistently improve model accuracy achieved using whole-body images only. The presented method provides a successful alternative to direct measurement for obtaining anthropometric measurements required for customized inertia modeling. The noninvasive image-based approach is benefited by the potential for obtaining subject-specific measurements from large samples of subjects and elite athletic performers for whom time-consuming data collections may be undesirable.

scholarly journals Body mapping of sweating patterns of pre-pubertal children during intermittent exercise in a warm environment

2021 ◽  
Author(s):  
Leigh Arlegui ◽  
James W. Smallcombe ◽  
Damien Fournet ◽  
Keith Tolfrey ◽  
George Havenith
Keyword(s):  
Intermittent Exercise ◽  
Sweat Rate ◽  
The Body ◽  
Whole Body ◽  
Body Mapping ◽  
Warm Environment ◽  
The Mean ◽  
Lower Ratio ◽  
Hands And Feet ◽  
Sweating Patterns

Abstract Purpose To determine sweating responses of pre-pubertal children during intermittent exercise in a warm environment and create whole-body maps of regional sweat rate (RSRs) distribution across the body. Methods Thirteen pre-pubertal children; six girls and seven boys (8.1 ± 0.8 years) took part. Sweat was collected using the technical absorbent method in the last 5 min of a 30-min intermittent exercise protocol performed at 30 ℃, 40% relative humidity and 2 m·s−1 frontal wind. Results Mean gross sweat loss (GSL) was 126 ± 47 g·m−2·h−1 and metabolic heat production was 278 ± 50 W·m2. The lower anterior torso area had the lowest RSR with a median (IQR) sweat rate (SR) of 40 (32) g·m−2·h−1. The highest was the forehead with a median SR of 255 (163) g·m−2·h−1. Normalised sweat maps (the ratio of each region’s SR to the mean SR for all measured pad regions) showed girls displayed lower ratio values at the anterior and posterior torso, and higher ratios at the hands, feet and forehead compared to boys. Absolute SRs were similar at hands and feet, but girls sweated less in most other areas, even after correction for metabolic rate. Conclusion Pre-pubertal children have different RSRs across the body, also showing sex differences in sweat distribution. Distributions differ from adults. Hands and feet RSR remain stable, but SR across other body areas increase with maturation. These data can increase specificity of models of human thermoregulation, improve the measurement accuracy of child-sized thermal manikins, and aid companies during product design and communication.

scholarly journals Cone Beam CT (CBCT) Based Synthetic CT Generation Using Deep Learning Methods for Dose Calculation of Nasopharyngeal Carcinoma Radiotherapy

2021 ◽  
Vol 20 ◽  
pp. 153303382110624
Author(s):  
Xudong Xue ◽  
Yi Ding ◽  
Jun Shi ◽  
Xiaoyu Hao ◽  
Xiangbin Li ◽  
...  
Keyword(s):  
Deep Learning ◽  
Mean Squared Error ◽  
Similarity Index ◽  
Dose Calculation ◽  
Absolute Error ◽  
Learning Methods ◽  
Index Analysis ◽  
Gamma Index ◽  
The Mean ◽  
Synthetic Ct

Objective: To generate synthetic CT (sCT) images with high quality from CBCT and planning CT (pCT) for dose calculation by using deep learning methods. Methods: 169 NPC patients with a total of 20926 slices of CBCT and pCT images were included. In this study the CycleGAN, Pix2pix and U-Net models were used to generate the sCT images. The Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Peak Signal to Noise Ratio (PSNR), and Structural Similarity Index (SSIM) were used to quantify the accuracy of the proposed models in a testing cohort of 34 patients. Radiation dose were calculated on pCT and sCT following the same protocol. Dose distributions were evaluated for 4 patients by comparing the dose-volume-histogram (DVH) and 2D gamma index analysis. Results: The average MAE and RMSE values between sCT by three models and pCT reduced by 15.4 HU and 26.8 HU at least, while the mean PSNR and SSIM metrics between sCT by different models and pCT added by 10.6 and 0.05 at most, respectively. There were only slight differences for DVH of selected contours between different plans. The passing rates of 2D gamma index analysis under 3 mm/3% 3 mm/2%, 2 mm/3%and 2 mm/2% criteria were all higher than 95%. Conclusions: All the sCT had achieved better evaluation metrics than those of original CBCT, while the performance of CycleGAN model was proved to be best among three methods. The dosimetric agreement confirmed the HU accuracy and consistent anatomical structures of sCT by deep learning methods.

scholarly journals Model of metameric locomotion in smooth active directional filaments with curvature fluctuations

2021 ◽  
Author(s):  
Guangle Du ◽  
Sunita Kumari ◽  
Fangfu Ye ◽  
Rudolf Podgornik
Keyword(s):  
Theoretical Model ◽  
Planck Equation ◽  
The Body ◽  
Whole Body ◽  
Langevin Equations ◽  
Mean Square ◽  
Fokker Planck Equation ◽  
Directional Motion ◽  
The Mean ◽  
Fokker Planck

Abstract Locomotion in segmented animals, such as annelids and myriapods (centipedes and millipedes), is generated by a coordinated movement known as metameric locomotion, which can be also implemented in robots designed to perform specific tasks. We introduce a theoretical model, based on an active directional motion of the head segment and a passive trailing of the rest of the body segments, in order to formalize and study the metameric locomotion. The model is specifically formulated as a steered Ornstein-Uhlenbeck curvature process, preserving the continuity of the curvature along the whole body filament, and thus supersedes the simple active Brownian model, which would be inapplicable in this case. We obtain the probability density by analytically solving the Fokker-Planck equation pertinent to the model. We also calculate explicitly the correlators, such as the mean-square orientational fluctuations, the orientational correlation function and the mean-square separation between the head and tail segments, both analytically either via the Fokker-Planck equation or directly by either solving analytically or implementing it numerically from the Langevin equations. The analytical and numerical results coincide. Our theoretical model can help understand the locomotion of metameric animals and instruct the design of metameric robots.

scholarly journals Comparison of Gray Values of Cone-beam Computed Tomography With Hounsfield Units of Multislice Computed Tomography Using a U-net Based Network

2020 ◽  
Author(s):  
Jingbo Wang ◽  
Tao Xiaofeng ◽  
Zhao Liang ◽  
Yuan Jing ◽  
Liu Chang ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Virus Disease ◽  
Similarity Index ◽  
Structural Similarity ◽  
Absolute Error ◽  
The Body ◽  
Cone Beam ◽  
High Attenuation ◽  
Synthetic Ct

Abstract Background：Dental departments generally employ cone-beam computed tomography (CBCT) instead of conventional computed tomography (CT), due to its lower price, smaller dosage, and high spatial resolution. During the corona virus disease 2019 (COVID-19) outbreak, CBCT is highly recommended to replace intraoral radiography because it greatly reduces the risk of exposure to salivary droplets. However, CBCT's inability to quantitatively measure tissue attenuation limits its application in differential diagnosis. Methods:We employed a U-Net based network to generate synthetic CT from dental CBCT. The deep neural network can be trained end-to-end to learn the complex mapping between CBCT and CT values. By the U-Net architecture, low-level and high-level features are both utilized to get fine detailed synthetic CT. We applied our method on the collected dataset contains 62 patients. Results:Experimental results on four metrics -- mean absolute error (MAE), root-mean-square error (RMSE), structural similarity index (SSIM), and peak-signal-to-noise ratio (PSNR) -- showed significant improvement of the synthetic CT compared to the original CBCT data. The MAE and RMSE improvement percentages are 64.44% and 66.44%.The MAE level of synthetic CT for most of the tissues are small enough to separate most important tissues,including dentin and cancellous bone, dentin and root canal，implants and cortical bone.Conclusions:CBCT and synthetic CT values can be used to distinguish different high-attenuation structures that are of interest to dentists. The application of CBCT assisted by this U-net based network in medical imaging of other parts of the body is promising.

scholarly journals Eye Movements and Body Images

1964 ◽  
Vol 9 (4) ◽  
pp. 336-344 ◽  
Author(s):  
E. Llewellyn Thomas ◽  
Eugene Stasiak
Keyword(s):  
Eye Movements ◽  
Visual Attention ◽  
Eye Movement ◽  
Psychiatric Patients ◽  
External World ◽  
The Body ◽  
The Other ◽  
Body Images ◽  
The Face ◽  
The Mean

The eye-movement patterns of nine hospitalized psychiatric patients were compared with those of ten non-patients when looking at pictures of themselves and others. There were highly significant differences between both the mean fixation times of the two groups and also between the area of the body to which they paid the most attention. The mean fixation times of all the non-patients grouped closely around 0.61 seconds whereas the patients varied between 0.12 seconds and 0.47 seconds and 0.72 seconds and 1.04 seconds. Non-patients looked at all body levels, but spent much more time looking at the face. Patients on the other hand paid much more visual attention to the body and tended to avoid the face. It is suggested that the variability in the fixation times and the tendency to avoid the face reflects a mechanism in the patient which is tending to avoid receiving information about certain aspects of the external world.

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