Dimensional Images Research Articles

Associations of dietary patterns and longitudinal brain-volume change in Japanese community-dwelling adults: results from the national institute for longevity sciences-longitudinal study of aging

BackgroundThe association of dietary patterns and longitudinal changes in brain volume has rarely been investigated in Japanese individuals. We prospectively investigated this association in middle-aged and older Japanese community-dwelling adults.MethodsData with a 2-year follow-up from the sixth wave (July 2008 to July 2010; baseline) to the seventh (July 2010 to July 2012; follow-up) of the National Institute for Longevity Sciences-Longitudinal Study of Aging project were analyzed. Dietary intake was assessed using a 3-day dietary record, and longitudinal volume changes (%) in the total gray matter (TGM), total white matter, and frontal, parietal, occipital, temporal, and insular lobes were assessed using 3-dimensional T1 magnetic resonance imaging scans. Multiple factor analysis and hierarchical clustering revealed sex-specific dietary patterns. Associations between dietary patterns and annual brain-volume changes (%) were evaluated using general linear models adjusted for age, apoprotein E genotype, body mass index, medical history, lifestyle behaviors, socioeconomic factors, and energy intake.ResultsAmong the 1636 participants (age: 40.3–89.2 years), three dietary patterns were determined for men (n = 815; Western; Vegetable-Fruit-Dairy; and Traditional Japanese diets) and women (n = 821; Western; Grain-Vegetable-Fruit; and Traditional Japanese diets). Compared to women following the Western diet, those on the Traditional Japanese diet had less TGM atrophy. Multivariable-adjusted β (95% confidence interval) of the annual change (%) of TGM was − 0.145 (-0.287 to -0.002; P = 0.047), which correlated with reduced parietal lobe atrophy. No association between dietary pattern and brain atrophy was observed in men.ConclusionsAdherence to healthy dietary patterns, with higher consumption of whole grains, seafood, vegetables, fruits, mushrooms, soybean products, and green tea, potentially confers a protective effect against brain atrophy in middle-aged and older Japanese women but not in men. Further research to confirm these results and ascertain the underlying mechanisms is required. This study highlights the importance of sex-specific effects on the relationship between dietary patterns and brain health in diverse populations.

Spot Spine, a freely available ImageJ plugin for 3D detection and morphological analysis of dendritic spines.

Dendritic spines are tiny protrusions found along the dendrites of neurons, and their number is a measure of the density of synaptic connections. Altered density and morphology is observed in several pathologies, and spine formation as well as morphological changes correlate with learning and memory. The detection of spines in microscopy images and the analysis of their morphology is therefore a prerequisite for many studies. We have developed a new open-source, freely available, plugin for ImageJ/FIJI, called Spot Spine, that allows detection and morphological measurements of spines in three dimensional images. Local maxima are detected in spine heads, and the intensity distribution around the local maximum is computed to perform the segmentation of each spine head. Spine necks are then traced from the spine head to the dendrite. Several parameters can be set to optimize detection and segmentation, and manual correction gives further control over the result of the process. The plugin allows the analysis of images of dendrites obtained with various labeling and imaging methods. Quantitative measurements are retrieved including spine head volume and surface, and neck length. The plugin and instructions for use are available at https://imagej.net/plugins/spot-spine.

Misidentification of the True Aortic Annulus With 2-dimensional Echocardiography: A Critical Appraisal Using 3-Dimensional Imaging

ObjectivesThis study aimed to evaluate the accuracy of identifying the 'true aortic valve (AV) annulus' using 2-dimensional (2D) echocardiography with the aim of highlighting potential misidentification issues in clinical practice. DesignAn observational study employing 3-dimensional (3D) datasets to generate 2D images of the AV annulus for analysis. SettingThe study was conducted in an academic medical center. ParticipantsThree-dimensional transesophageal echocardiography (3D TEE) datasets were obtained from 11 patients with normal AV and aortic root anatomies, undergoing coronary artery bypass surgery. Attending anaesthesiologists certified by the national board of echocardiography (NBE) were subsequently approached to participate in this study. InterventionsTwo images per patient were generated from 3D datasets, reflecting the mid-esophageal long-axis view of the AV: a 'True AV Annulus Image' and an 'Off-Axis Image'. A survey was distributed to NBE certified perioperative echocardiographers across 12 academic institutions to identify the 'true AV annulus' from these images. Measurements and Main ResultsThe survey, completed by 45 qualified respondents, revealed a significant misidentification rate of the 'true AV annulus', with only 36.8% of responses correctly identifying it. The rate of correct identification varied across image sets, with 44.4% of participants unable to correctly identify any 'true AV annulus' image. ConclusionsThe study highlights the limitations of 2D echocardiography in accurately identifying the 'true AV annulus' in complex 3D structures like the aortic root. The findings suggest a need for greater reliance on advanced imaging modalities, such as 3D echocardiography, to improve accuracy in clinical practice.

Three-dimensional volume rendering ultrasound for assessing placenta accreta spectrum severity and discriminating it from simple scar dehiscence

Prenatal ultrasound discrimination between placenta accreta spectrum and scar dehiscence with underlying nonadherent placenta is challenging both prenatally and intraoperatively, which often leads to overtreatment. In addition, accurate prenatal prediction of surgical difficulty and morbidity in placenta accreta spectrum is difficult, which precludes appropriate multidisciplinary planning. The advent of advanced 3-dimensional volume rendering and contrast enhancement techniques in modern ultrasound systems provides a comprehensive prenatal assessment, revealing details that are not discernible in traditional 2-dimensional imaging. This study aimed to evaluate the use of 3-dimensional volume rendering ultrasound techniques in determining the severity of placenta accreta spectrum and distinguishing between placenta accreta spectrum and scar dehiscence with underlying nonadherent placenta. A prospective, cohort study was conducted between July 2022 and July 2023 in the fetal medicine unit of Dr Soetomo Academic General Hospital, Surabaya, Indonesia. All pregnant individuals with anterior low-lying placenta or placenta previa with a previous caesarean section who were referred with suspicion of placenta accreta spectrum were consented and screened using the standardised 2-dimensional and Doppler ultrasound imaging. Additional 3-dimensional volumes were obtained from the sagittal section of the uterus with a filled urinary bladder. These were analyzed by rotating the region of interest to be perpendicular to the uterovesical interface. The primary outcomes were the clinical and histologic severity in the cases of placenta accreta spectrum and correct diagnosis of dehiscence with nonadherent placenta underneath. The strength of association between ultrasound and clinical outcomes was determined. Multivariate logistic regression analyses and diagnostic testing of accuracy were used to analyze the data. A total of 70 patients (56 with placenta accreta spectrum and 14 with scar dehiscence) were included in the analysis. Multivariate logistic regression of all 2-dimensional and 3-dimensional signs revealed the 3-dimensional loss of clear zone (P<.001) and the presence of bridging vessels on 2-dimensional Doppler ultrasound (P=.027) as excellent predictors in differentiating scar dehiscence and placenta accreta spectrum. The 3-dimensional loss of clear zone demonstrated a high diagnostic accuracy with an area under the curve of 0.911 (95% confidence interval, 0.819-1.002), with a sensitivity of 89.3% (95% confidence interval, 78.1-95.97%) and specificity of 92.9% (95% confidence interval, 66.1-99.8%). The presence of bridging vessels on 2-dimensional Doppler demonstrated an area under the curve of 0.848 (95% confidence interval, 0.714-0.982) with a sensitivity of 91.1% (95% confidence interval, 80.4-97.0%) and specificity of 78.6% (95% confidence interval, 49.2-95.3%). A subgroup analysis among the placenta accreta spectrum group revealed that the presence of a 3-dimensional disrupted bladder serosa with obliteration of the vesicouterine space was associated with vesicouterine adherence (P<.001). Three-dimensional volume rendering ultrasound is a promising tool for effective discrimination between scar dehiscence with underlying nonadherent placenta and placenta accreta spectrum. It also shows potential in predicting the clinical severity with urinary bladder involvement in cases of placenta accreta spectrum.

EVALUASI CITRA RUMAH SAKIT DI RUMAH SAKIT PKU MUHAMMADIYAH BANTUL

Background: DIY province has 70 hospitals, Bantul district has 10 hospitals that serve 859.968 inhabitants with 793 beds. Although the amount of hospital or beds was not enough, it was important for hospital to keep their image, it’s necessary to maintain or expand their market confidence.&#x0D; Method: It’s Quantitative-Qualitative study, cross-sectional survey and descriptive analytic. The quantitative used for determining images position, It’s used questionnaire to 118 respondents with purposive sampling methode. The qualitative used for supporting quantitative result and became reasons for improvements of dimensional image. Data Analysis used the differential semantic, four instruments and theory of marketing strategic.&#x0D; Result and discussion: There were 23 dimensions of hospital image, all of them show good images, doctors are skilled and experienced (98%.), skilled nursing (92%), professionalism (97%), neat and clean officer’s clothes (92%); organized and comfortable rooms (81%), building and rooms cleanliness (86%); complete facilities (85%), comfortable and hygine facilities (81%); complete medical equipments (88%), complete pharmaceuticals (95%); uncomplicated procedures (93%), officer’s timeliness (76%); sufficient consultation time (83%), attention and sympathy officers (92%), willingness to respond complaints (97%), hospitality (95%); appropriate price (95%), ease of insurance used (88%); strategic location and affordable (97%), inpatient room easily obtained (59%), ease to see the doctor (83%), information access (98%), understandly boards (76%). Image improvement priorities: timeliness officer, ease to see the doctor, adequacy of consultation time, board reconstruction, inpatient room additions, comfortable and hygine facilities, organized and comfortable rooms.&#x0D; Conclusions: All of hospital images were good. There were 7 dimension still need to be improved.

Application of Freehand 3D Ultrasound Guidance in Percutaneous Transluminal Angioplasty for Autogenous Arteriovenous Fistula Stenosis

Objective: Using freehand three dimensional (3D) ultrasound imaging to evaluate arteriovenous fistula stenosis. Comparing the value of freehand 3D ultrasound and Doppler ultrasound in the application of percutaneous transluminal angioplasty (PTA) treatment for stenosis of an arteriovenous fistula. Methods: A retrospective analysis was conducted on 34 patients with arteriovenous fistula (AVF) stenosis who were treated at the 903RD Hospital of PLA and the Kidney Center of Zhejiang Provincial People's Hospital from August 2021 to August 2022. Based on the different types of surgical assistance, the patients were divided into two groups: the Doppler ultrasound group (Group A, n = 17) and the freehand 3D ultrasound imaging group (Group B, n = 17). Freehand 3D ultrasound and Doppler ultrasound were used to assess the narrowing of arteriovenous fistulas, and images and relevant data were collected before and after the PTA procedure. The differences in the time of puncture and sheath placement, guidewire insertion time, the duration of the procedure, complications, and methods to measure stenosis were compared between the two groups of patients, as well as the technical success rate, the initial patency rate, and the primary patency rates at 1, 3, 6 and 9 months post-surgery. This study discusses the clinical efficacy of using these two types of ultrasound to assist in the PTA treatment of arteriovenous fistula stenosis. Results: The differences in baseline demographics between the conventional ultrasound group (Group A) and the 3D ultrasound group (Group B) were not statistically significant (p &gt; 0.05). The intraoperative guidewire insertion time (4.647 ± 1.347 min vs. 2.824 ± 0.326 min) and the operating times (75.941 ± 7.557 min vs. 59.824 ± 8.175 min) between the two groups were statistically significant (t = 2.788, 3.069, p &lt; 0.01). The technical success rates for the two groups were 94.1% vs. 100%, not statistically significant (t = 1.03, p = 0.31). The first-time patency rates were 88.2% vs. 94.1%, with no statistically significant difference (t = 0.366, p = 0.545). No complications occurred in Group A, while one case of hematoma occurred postoperatively in Group B, with an incidence of 5.9% (1/17), which was not statistically significant (t = 1.03, p &gt; 0.05). Comparing the primary patency rates at 1, 3, 6 and 9 months post-surgery between Groups A and B, there were no statistically significant differences (p &gt; 0.05). However, the patency rates at different time points for Group B were consistently higher than Group A (94.1%, 82.4%, 82.4%, 82.4% vs. 88.2%, 82.4%, 76.5%, 76.5%). Conclusion: Freehand 3D ultrasound imaging can provide more intuitive, high-resolution, and high-definition three-dimensional images, clearly defining the lesion site and vascular structures. Its accuracy in assessing complications of arteriovenous fistulas is similar to that with conventional ultrasound. When used as an adjunct to PTA treatment, its efficacy is equivalent. It can significantly reduce guidewire insertion time and operation time, decrease postoperative recovery time, and alleviate the patients' concerns regarding surgical risks. It can be considered a new method for diagnosing, treating, and patients with AVF stenosis.

Automated anatomical landmark detection on 3D facial images using U-NET-based deep learning algorithm.

Facial anthropometry based on 3-dimensional (3D) imaging technology, or 3D photogrammetry, has gained increasing popularity among surgeons. It outperforms direct measurement and 2-dimensional (2D) photogrammetry because of many advantages. However, a main limitation of 3D photogrammetry is the time-consuming process of manual landmark localization. To address this problem, this study developed a U-NET-based deep learning algorithm to enable automated and accurate anatomical landmark detection on 3D facial models. The main structure of the algorithm stacked 2 U-NETs. In each U-NET block, we used 3×3 convolution kernel and rectified linear unit (ReLU) as activation function. A total of 200 3D images of healthy cases, acromegaly patients, and localized scleroderma patients were captured by Vectra H1 handheld 3D camera and input for algorithm training. The algorithm was tested to detect 20 landmarks on 3D images. Percentage of correct key points (PCK) and normalized mean error (NME) were used to evaluate facial landmark detection accuracy. Among healthy cases, the average NME was 1.4 mm. The PCK reached 90% when the threshold was set to the clinically acceptable limit of 2 mm. The average NME was 2.8 and 2.2 mm among acromegaly patients and localized scleroderma patients, respectively. This study developed a deep learning algorithm for automated facial landmark detection on 3D images. The algorithm was innovatively validated in 3 different groups of participants. It achieved accurate landmark detection and improved the efficiency of 3D image analysis.

Bridging New Observational Capabilities and Process-Level Simulation: Insights into Aerosol Roles in the Earth System

Abstract The spatial distribution of ambient aerosol particles significantly impacts aerosol–radiation–cloud interactions, which contribute to the largest uncertainty in global anthropogenic radiative forcing estimations. However, the atmospheric boundary layer and lower free troposphere have not been adequately sampled in terms of spatiotemporal resolution, hindering a comprehensive characterization of various atmospheric processes and impeding our understanding of the Earth system. To address this research data gap, we have leveraged the development of uncrewed aerial systems (UAS) and advanced measurement techniques to obtain mesoscale spatial data on aerosol microphysical and optical properties around the U.S. Southern Great Plains (SGP) atmospheric observatory. Our study also benefits from state-of-the-art laboratory facilities that include three-dimensional molecular imaging techniques enabled by secondary ion mass spectrometry and nanogram-level chemical composition analysis via micronebulization aerosol mass spectrometry. Through our study, we have developed a framework for observation–modeling integration, enabling an examination of how various assumptions about the organic–inorganic components mixing state, inferred from chemical analysis, affect clouds and radiation in observation-constrained model simulations. By integrating observational constraints (derived from offline chemical analysis of the aerosol surface using collected samples) with in situ UAS observations, we have identified a prominent role of organic-enriched nanometer layers located at the surface of aerosol particles in determining profiles of aerosol optical and hygroscopic properties over the SGP observatory. Furthermore, we have improved the agreement between predicted clouds and ground-based cloud lidar measurements. This UAS–model–laboratory integration exemplifies how these new advanced capabilities can significantly enhance our understanding of aerosol–radiation–cloud interactions.

Intelligent extraction of road cracks based on vehicle laser point cloud and panoramic sequence images

In light of the limited efficacy of conventional methods for identifying pavement cracks and the absence of comprehensive depth and location data in two-dimensional photographs, this study presents an intelligent strategy for extracting road cracks. This methodology involves the integration of laser point cloud data obtained from a vehicle-mounted system and a panoramic sequence of images. The study employs a vehicle-mounted LiDAR measurement system to acquire laser point cloud and panoramic sequence image data simultaneously. A convolutional neural network is utilized to extract cracks from the panoramic sequence image. The extracted sequence image is then aligned with the laser point cloud, enabling the assignment of RGB information to the vehicle-mounted three dimensional (3D) point cloud and location information to the two dimensional (2D) panoramic image. Additionally, a threshold value is set based on the crack elevation change to extract the aligned roadway point cloud. The three-dimensional data pertaining to the cracks can be acquired. The experimental findings demonstrate that the use of convolutional neural networks has yielded noteworthy outcomes in the extraction of road cracks. The utilization of point cloud and image alignment techniques enables the extraction of precise location data pertaining to road cracks. This approach exhibits superior accuracy when compared to conventional methods. Moreover, it facilitates rapid and accurate identification and localization of road cracks, thereby playing a crucial role in ensuring road maintenance and traffic safety. Consequently, this technique finds extensive application in the domains of intelligent transportation and urbanization development. The technology exhibits significant promise for use in the domains of intelligent transportation and city development.

The role of multimodal ultrasound in diagnosis of fetal bowel dilatation and prediction of adverse neonatal outcomes: A study of 86 cases in a series of 43,562 births

ObjectiveTo investigate the diagnostic utility of multimodal ultrasound for fetal bowel dilatation (FBD) in different parts of the bowel and to examine its prognostic potential in FBD. MethodsThis retrospective study analyzed 86 fetuses with a dilated bowel identified via ultrasound in a 10-month postnatal follow-up. Both two- and three dimensional (2D and 3D, respectively) ultrasound volume imaging were used to characterize dilation across different bowel sections. The optimal intestinal diameter cut-off values for pathological bowel dilatation were determined and a predictive model for neonatal surgery was developed. ResultsThe 86 cases of dilatation were distributed as follows: duodenal (n = 36); jejunum/ileum (n = 35); and colonic (n = 15). Duodenal dilatations presented the earliest during pregnancy compared to the other 2 groups (24.4 versus [vs.] 29 vs. 33.7 weeks respectively; p < 0.05). Cases with small intestinal dilatation were delivered earlier than those with colonic dilatation (p < 0.05). Infants with duodenal dilatation had the lowest birth weight and the highest rate of multi-system abnormalities (30.6% vs. 5.7% vs. 20%; p < 0.001). More than one-half of the multi-system abnormalities had chromosomal abnormalities (multiple, 54% vs. single, 12.5%; p = 0.015). There were 2 stillbirths, 24 induced labors, 44 postnatal surgeries, and 18 normal cases after birth. In predicting adverse neonatal outcomes of jejunum/ileum dilatation using a cut-off value of 15.5 mm small intestine diameter, sensitivity was 81.5%, specificity was 62.5%, and the area under the receiver operating characteristic curve (AUC) was 0.762 (p < 0.05). For colonic dilatation, using a cut-off value of 21.5 mm colon diameter: sensitivity was 83.3%, specificity was 77.8%, and AUC was 0.861 (p < 0.05). In detecting jejunum/ileum and colonic obstruction, 3D ultrasound demonstrated significantly better diagnostic efficiency than 2D ultrasound (p < 0.05). Using the backward stepwise selection method, a predictive model for neonatal surgery in patients with jejunum/ileum and colonic dilatation was established: logit (P) = −1.58 + (2.32 × polyhydramnios) +(2.0 × ascites) +(1.14 × hyperechogenic bowel). The AUC for the prediction model was 0.874 (p < 0.05), with 76% sensitivity and 94.1% specificity. ConclusionsDuodenal dilatation occurred earlier, with a higher incidence of chromosomal abnormalities and multi-system abnormalities than dilatation of other parts of the bowel. 3D ultrasound played an important role in the detection of jejunum/ileum and colon obstructions. Clinical signs, including polyhydramnios, ascites, and strong echoes in the intestine, can be used to predict neonatal surgery.

Multimodal image fusion-assisted endoscopic evacuation of spontaneous intracerebral hemorrhage

PurposeAlthough traditional craniotomy (TC) surgery has failed to show benefits for the functional outcome of intracerebral hemorrhage (ICH). However, a minimally invasive hematoma removal plan to avoid white matter fiber damage may be a safer and more feasible surgical approach, which may improve the prognosis of ICH. We conducted a historical cohort study on the use of multimodal image fusion-assisted neuroendoscopic surgery (MINS) for the treatment of ICH, and compared its safety and effectiveness with traditional methods. MethodsThis is a historical cohort study involving 241 patients with cerebral hemorrhage. Divided into MINS group and TC group based on surgical methods. Multimodal images (CT skull, CT angiography, and white matter fiber of MRI diffusion-tensor imaging) were fused into 3 dimensional images for preoperative planning and intraoperative guidance of endoscopic hematoma removal in the MINS group. Clinical features, operative efficiency, perioperative complications, and prognoses between 2 groups were compared. Normally distributed data were analyzed using t-test of 2 independent samples, Non-normally distributed data were compared using the Kruskal-Wallis test. Meanwhile categorical data were analyzed via the Chi-square test or Fisher’s exact test. All statistical tests were two-sided, and p < 0.05 was considered statistically significant. ResultsA total of 42 patients with ICH were enrolled, who underwent TC surgery or MINS. Patients who underwent MINS had shorter operative time (p < 0.001), less blood loss (p < 0.001), better hematoma evacuation (p = 0.003), and a shorter stay in the intensive care unit (p = 0.002) than patients who underwent TC. Based on clinical characteristics and analysis of perioperative complications, there is no significant difference between the 2 surgical methods. Modified Rankin scale scores at 180 days were better in the MINS than in the TC group (p = 0.014). ConclusionsCompared with TC for the treatment of ICH, MINS is safer and more efficient in cleaning ICH, which improved the prognosis of the patients. In the future, a larger sample size clinical trial will be needed to evaluate its efficacy.

Can 3-dimensional cranial ultrasound be used to successfully reconstruct a 2-dimensional image without compromising on image quality in a neonatal population?

Cranial ultrasound is frequently performed in neonatal intensive care units and acquiring 2-dimensional (D) images requires significant training. Three-D ultrasound images can be acquired semi-automatically. This proof-of-concept study aimed to demonstrate that 3-D study image quality compares well with 2-D. If this is successful, 3-D images could be acquired in remote areas and read remotely by experts. This was a prospective study of 20 neonates, who underwent both routine 2-D and 3-D cranial ultrasounds. Images were reconstructed into standard views extracted from the 3-D volume and evaluated by three radiologists blinded to the acquisition method. The radiologists assessed for the presence of anatomical landmarks and overall image quality. More anatomical structures were identified in the 3-D studies (P<0.01). There was a trend that 3-D ultrasound demonstrated better image quality in the coronal plane, and 2-D in the sagittal plane, only reaching statistical significance for two coronal views and two sagittal views. Overall, this study has demonstrated that 3-D cranial ultrasound performs similarly to 2-D and could be implemented into neonatal practice.

Orbital Development in Children with Retinoblastoma: An Imaging-Based Study

ABSTRACT Purpose To examine whether children treated for Retinoblastoma (Rb) have impaired orbital development. Methods A retrospective case series was performed among children with Rb treated at a single medical center from 2004 to 2020. Orbital volumes and measurements were assessed by 3-dimensional image processing software. The main outcome measures were differences in orbital growth between Rb and non-Rb eyes assessed at last follow-up. Results Among 44 patients included (mean age 16.09 ± 18.01 months), a positive correlation between age and orbital volume was observed only in the uninvolved, healthy eyes (p = .03). In unilateral cases, orbital growth in the horizontal, vertical, and depth planes was smaller on the affected side compared to the healthy eyes (p < .05). Orbits that underwent enucleation showed decreased growth over time compared to those treated conservatively (p = .017). Conclusions Orbital growth rate is slower in the orbits of children treated for Rb compared to healthy orbits. Enucleation negatively affects orbital growth.

13C MRI of hyperpolarized pyruvate at 120 µT

Nuclear spin hyperpolarization increases the sensitivity of magnetic resonance dramatically, enabling many new applications, including real-time metabolic imaging. Parahydrogen-based signal amplification by reversible exchange (SABRE) was employed to hyperpolarize [1-13C]pyruvate and demonstrate 13C imaging in situ at 120 µT, about twice Earth’s magnetic field, with two different signal amplification by reversible exchange variants: SABRE in shield enables alignment transfer to heteronuclei (SABRE-SHEATH), where hyperpolarization is transferred from parahydrogen to [1-13C]pyruvate at a magnetic field below 1 µT, and low-irradiation generates high tesla (LIGHT-SABRE), where hyperpolarization was prepared at 120 µT, avoiding magnetic field cycling. The 3-dimensional images of a phantom were obtained using a superconducting quantum interference device (SQUID) based magnetic field detector with submillimeter resolution. These 13C images demonstrate the feasibility of low-field 13C metabolic magnetic resonance imaging (MRI) of 50 mM [1-13C]pyruvate hyperpolarized by parahydrogen in reversible exchange imaged at about twice Earth’s magnetic field. Using thermal 13C polarization available at 120 µT, the same experiment would have taken about 300 billion years.

A dynamic individual method for yak heifer live body weight estimation using the YOLOv8 network and body parameter detection algorithm

Live body weight (LBW) is one of the most important parameters for supervising the growth and development of livestock. The yak (Bos grunniens) is a special species of cattle that lives on the Qinghai-Tibetan Plateau. Yaks are more untamed than regular cattle breeds, thus it is more challenging to measure their LBW. In this study, a YOLOv8 yak detection and LBW estimation models were used to automatically estimate yak LBW in real-time. First, the proper posture (normal posture) and individual yak identification was confirmed and then the YOLOv8 detection model was used for LBW estimation from 2-dimensional (2D) images. Yak LBW was estimated through yak body parameter extraction and a simple linear regression between the estimated yak LBW and the actual measured yak LBW. The results showed that the overall detection performance of yak normal yak posture was described by precision, recall, and mean Average Precision 50 (mAP50) indicators, reaching 81.8, 86.0, and 90.6%, respectively. The best yak identification results were represented by precision, recall, and mAP50 values of 97.8, 96.4, and 99.0%, respectively. The yak LBW estimation model achieved better results for the 12 mo old yaks with shorter hair with R2, root mean square error (RMSE), mean absolute percentage error (MAPE), and Multiple R values of 0.96, 2.43 kg, 1.69%, and 0.98, respectively. The results demonstrate that yak LBW can be estimated and monitored in real-time using this approach. This study has the potential to be used for daily yak LBW monitoring in an unstressed manner and to save considerable labor resources for large-scale livestock farms. In the future, to reduce the limitations caused by the impacts of yak hair and light condition data sets of dairy cows and yaks of different ages will be used to improve and generalize the model.

Application of a Combinatorial Vortex Detection Algorithm on 2 Component 2 Dimensional Particle Image Velocimetry Data to Characterize the Wake of an Oscillating Wing

To investigate the vortical wake pattern generated by water flow past an oscillating symmetric airfoil, using experimental velocity fields from particle image velocimetry (PIV), a novel combinatorial vortex detection (CVD) algorithm is developed. The primary goal is to identify and characterize vortices within the wake. Experimental flows introduce complexities not present in numerical simulations, posing challenges for vortex detection. The proposed CVD approach offers a more robust alternative, excelling in both vortex detection and quantification of essential parameters, unlike widely-used methods such as Q-criterion, λ2-criterion, and Δ-criterion, which rely on subjective and arbitrary thresholds resulting in uncertainty. The CVD algorithm effectively characterizes the airfoil wake, identifying and analyzing vortices aligning with the Burgers model. This research enhances understanding of wake phenomena and showcases the algorithm’s potential as a valuable tool for vortex detection and characterization, particularly for experimental fluid dynamics. It provides a comprehensive, robust, and non-arbitrary approach, overcoming limitations of traditional methods and opening new avenues for studying complex flows.

Intraoperative Videogrammetry and Photogrammetry for Photorealistic Neurosurgical 3-Dimensional Models Generated Using Operative Microscope: Technical Note.

Intraoperative orientation during microsurgery has a prolonged learning curve among neurosurgical residents. Three-dimensional (3D) understanding of anatomy can be facilitated with realistic 3D anatomic models created from photogrammetry, where a series of 2-dimensional images is converted into a 3D model. This study implements an algorithm that can create photorealistic intraoperative 3D models to exemplify important steps of the operation, operative corridors, and surgical perspectives. We implemented photograph-based and video-based scanning algorithms for uptakes using the operating room (OR) microscope, targeted for superficial structures, after surgical exposure, and deep operative corridors, in cranial microsurgery. The algorithm required between 30-45 photographs (superficial scanning), 45-65 photographs (deep scanning), or approximately 1 minute of video recording of the entire operative field to create a 3D model. A multicenter approach in 3 neurosurgical departments was applied to test reproducibility and refine the method. Twenty-five 3D models were created of some of the most common neurosurgical approaches-frontolateral, pterional, retrosigmoid, frontal, and temporal craniotomy. The 3D models present important steps of the surgical approaches and allow rotation, zooming, and panning of the model, enabling visualization from different surgical perspectives. The superficial and medium depth structures were consistently presented through the 3D models, whereas scanning of the deepest structures presented some technical challenges, which were gradually overcome with refinement of the image capturing process. Intraoperative photogrammetry is an accessible method to create 3D educational material to show complex anatomy and demonstrate concepts of intraoperative orientation. Detailed interactive 3D models, displaying stepwise surgical case-based anatomy, can be used to help understand details of the operative corridor. Further development includes refining or automatization of image acquisition intraoperatively and evaluation of other applications of the resulting 3D models in training and surgical planning.

Distal planar rotary scanner for endoscopic optical coherence tomography.

Optical coherence tomography (OCT) is becoming a more common endoscopic imaging modality for detecting and treating disease given its high resolution and image quality. To use OCT for 3-dimensional imaging of small lumen, embedding an optical scanner at the distal end of an endoscopic probe for circumferential scanning the probing light is a promising way to implement high-quality imaging unachievable with the conventional method of revolving an entire probe. To this end, the present work proposes a hollow and planar micro rotary actuator for its use as an endoscopic distal scanner. A miniaturized design of this ferrofluid-assisted electromagnetic actuator is prototyped to act as a full 360° optical scanner, which is integrated at the tip of a fiber-optic probe together with a gradient-index lens for use with OCT. The scanner is revealed to achieve a notably improved dynamic performance that shows a maximum speed of 6500rpm, representing 325% of the same reported with the preceding design, while staying below the thermal limit for safe in-vivo use. The scanner is demonstrated to perform real-time OCT using human fingers as live tissue samples for the imaging tests. The acquired images display no shadows from the electrical wires to the scanner, given its hollow architecture that allows the probing light to pass through the actuator body, as well as the quality high enough to differentiate the dermis from the epidermis while resolving individual sweat glands, proving the effectiveness of the prototyped scanner design for endoscopic OCT application.

Accreditation of the handheld 3-dimensional scanner and conventional photo images for area measurement.

Accurate assessment of wound areas is crucial in making therapeutic decisions, as the prognosis and changes in the size of the wound over time play a significant role. An ideal assessment method should possess qualities such as speed, affordability, accuracy, user-friendliness for both patients and healthcare professionals, and suitability for daily clinical practice. This study aims to introduce a handheld 3-dimensional (3D) scanner and evaluate its accuracy in measuring wound areas. Engineers from the Industrial Technology Research Institute in Taiwan developed a handheld 3D scanner with the intention of extending its application to the medical field. A project was conducted to validate the accuracy of this 3D scanner. We utilized a smartphone (Asus ZenFone 2 with a 13-million-pixel rear camera), a digital single-lens reflex digital camera (Nikon, D5000, Tokyo, Japan), and the 3D scanner to repeatedly measure square papers of known size that were affixed to the curved surface of life-size facial mask or medical teaching breast models. The "Image J" software was employed for 2-dimensional image measurements, while the "3D Edit" software was used to assess the "area of interest" on 3D objects. By using square papers with predetermined dimensions, the measurement-associated error rate (ER) could be calculated for each image. Three repeated measurements were performed using the "Image J" software for each square paper. The ERs of the 3D scan images were all below 3%, with an average ER of 1.64% in this study. The close-up mode of the smartphone exhibited the highest ER. It was observed that as the area increased, the ER also increased in the digital single-lens reflex camera group. The extension distortion effect caused by the wide-angle lens on the smartphone may increase the ER. However, the definition of a healthy skin edge may vary, and different algorithms for calculating the measurement area are employed in various 3D measurement software. Therefore, further validation of their accuracy for medical purposes is necessary. Effective communication with software engineers and discussions on meeting clinical requirements are crucial steps in enhancing the functionality of the 3D scanner.

Wireless body area sensor networks based human activity recognition using deep learning

In the healthcare sector, the health status and biological, and physical activity of the patient are monitored among different sensors that collect the required information about these activities using Wireless body area network (WBAN) architecture. Sensor-based human activity recognition (HAR), which offers remarkable qualities of ease and privacy, has drawn increasing attention from researchers with the growth of the Internet of Things (IoT) and wearable technology. Deep learning has the ability to extract high-dimensional information automatically, making end-to-end learning. The most significant obstacles to computer vision, particularly convolutional neural networks (CNNs), are the effect of the environment background, camera shielding, and other variables. This paper aims to propose and develop a new HAR system in WBAN dependence on the Gramian angular field (GAF) and DenseNet. Once the necessary signals are obtained, the input signals undergo pre-processing through artifact removal and median filtering. In the initial stage, the time series data captured by the sensors undergoes a conversion process, transforming it into 2-dimensional images by using the GAF algorithm. Then, DenseNet automatically makes the processes and integrates the data collected from diverse sensors. The experiment results show that the proposed method achieves the best outcomes in which it achieves 97.83% accuracy, 97.83% F-measure, and 97.64 Matthews correlation coefficient (MCC).