Real-time Vessel Research Articles

In vivo spatiotemporal characterizing diverse body transportation of optical labeled high immunity aluminium adjuvants with photoacoustic tomography

Vaccine development requires high-resolution, in situ, and visual adjuvant technology. To address this need, this work proposed a novel adjuvant labeling that involved indocyanine green (ICG) and bovine serum albumin (BSA) with self-assembled aluminium adjuvant (Alum), which was called BSA@ICG@Alum. This compound exhibited excellent photoacoustic properties and has been confirmed its safety, biocompatibility, high antigen binding efficiency, and superior induction of immune response. Photoacoustic tomography (PAT) tracked the distribution of Alum in lymph nodes (LNs) and lymphatic vessels in real time after diverse injection modalities. The non-invasive imaging approach revealed that BSA@ICG@Alum was transported to the draining LNs 60 min after intramuscular injection and to distal LNs within 30 min after lymph node injection. In conclusion, PAT enabled real-time three-dimensional and quantitative visualization, thus offering a powerful tool for advancing vaccine design by providing critical insights into adjuvant transport and immune system activation.

Real Time Vessel Detection Model Using Deep Learning Algorithms for Controlling a Barrier System

This study addresses marine pollution caused by debris entering the ocean through rivers. A physical and bubble barrier system has been developed to collect debris, but an effective identification and classification system for incoming vessels is needed. This study evaluates the effectiveness of deep learning models in identifying and classifying vessels in real time. The YOLO (You Only Look Once) v5 and v8 models are evaluated for vessel detection and classification. A dataset of 624 images representing 13 different types of vessels was created to train the models. The YOLOv8, featuring a new backbone network, outperformed the YOLOv5 model, achieving a high mean average precision (mAP@50) of 98.9% and an F1 score of 91.6%. However, YOLOv8’s GPU consumption increased by 116% compared to YOLOv5. The advantage of the proposed method is evident in the precision–confidence curve (PCC), where the accuracy peaks at 1.00 and 0.937 confidence, and in the achieved frames per second (fps) value of 84.7. These findings have significant implications for the development and deployment of real-time marine pollution control technologies. This study demonstrates that YOLOv8, with its advanced backbone network, significantly improves vessel detection and classification performance over YOLOv5, albeit with higher GPU consumption. The high accuracy and efficiency of YOLOv8 make it a promising candidate for integration into marine pollution control systems, enabling real-time identification and monitoring of vessels. This advancement is crucial for enhancing the effectiveness of debris collection systems and mitigating marine pollution, highlighting the potential for deep learning models to contribute to environmental preservation efforts.

Research on risk data analysis of hazardous chemical vessels based on stream computing

Abstract To effectively improve the safety supervision and information management level of vessels carrying hazardous chemicals, the maritime management department is promoting the construction of hazardous chemical vessel monitoring systems based on artificial intelligent technology for hazardous chemical terminals and shipping companies in their jurisdiction. It can identify specific risks and transmit the risk data in real-time to the data center. To analyze data in real-time, a risk data analysis platform for hazardous chemical vessels based on stream computing is designed and implemented. The platform acquires vessel automatic identification system (AIS), risk, basic information, and other data. Based on the stream computing of Flink, it evaluates the risk status of vessels in real time, counts the risk data, and displays the results in the form of charts. The analysis of risk data for hazardous chemical vessels helps maritime management departments to track the real-time navigation status of key vessels, timely identify potential safety hazards, and effectively improve the level and efficiency of safety supervision.

High-performance laser speckle contrast image vascular segmentation without delicate pseudo-label reliance

Laser speckle contrast imaging (LSCI) is a noninvasive, label-free technique that allows real-time investigation of the microcirculation situation of biological tissue. High-quality microvascular segmentation is critical for analyzing and evaluating vascular morphology and blood flow dynamics. However, achieving high-quality vessel segmentation has always been a challenge due to the cost and complexity of label data acquisition and the irregular vascular morphology. In addition, supervised learning methods heavily rely on high-quality labels for accurate segmentation results, which often necessitate extensive labeling efforts. Here, we propose a novel approach LSWDP for high-performance real-time vessel segmentation that utilizes low-quality pseudo-labels for nonmatched training without relying on a substantial number of intricate labels and image pairing. Furthermore, we demonstrate that our method is more robust and effective in mitigating performance degradation than traditional segmentation approaches on diverse style data sets, even when confronted with unfamiliar data. Importantly, the dice similarity coefficient exceeded 85% in a rat experiment. Our study has the potential to efficiently segment and evaluate blood vessels in both normal and disease situations. This would greatly benefit future research in life and medicine.

Advances in Vascular Diagnostics using Magnetic Particle Imaging (MPI) for Blood Circulation Assessment.

Rapid and accurate assessment of conditions characterized by altered blood flow, cardiac blood pooling, or internal bleeding is crucial for diagnosing and treating various clinical conditions. While widely used imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound offer unique diagnostic advantages, they fall short for specific indications due to limited penetration depth and prolonged acquisition times. Magnetic particle imaging (MPI), an emerging tracer-based technique, holds promise for blood circulation assessments, potentially overcoming existing limitations with reduction in background signals and high temporal and spatial resolution, below the millimeter scale. Successful imaging of blood pooling and impaired flow necessitates tracers with diverse circulation half-lives optimized for MPI signal generation. Recent MPI tracers show potential in imaging cardiovascular complications, vascular perforations, ischemia, and stroke. The impressive temporal resolution and penetration depth also position MPI as an excellent modality for real-time vessel perfusion imaging via functional MPI (fMPI). This review summarizes advancements in optimized MPI tracers for imaging blood circulation and analyzes the current state of pre-clinical applications. This work discusses perspectives on standardization required to transition MPI from a research endeavor to clinical implementation and explore additional clinical indications that may benefit from the unique capabilities of MPI.

Video-Based Identification and Prediction Techniques for Stable Vessel Trajectories in Bridge Areas.

In recent years, the global upswing in vessel-bridge collisions underscores the vital need for robust vessel track identification in accident prevention. Contemporary vessel trajectory identification strategies often integrate target detection with trajectory tracking algorithms, employing models like YOLO integrated with DeepSORT or Bytetrack algorithms. However, the accuracy of these methods relies on target detection outcomes and the imprecise boundary acquisition method results in erroneous vessel trajectory identification and tracking, leading to both false positives and missed detections. This paper introduces a novel vessel trajectory identification framework. The Co-tracker, a long-term sequence multi-feature-point tracking method, accurately tracks vessel trajectories by statistically calculating the translation and heading angle transformation of feature point clusters, mitigating the impact of inaccurate vessel target detection. Subsequently, vessel trajectories are predicted using a combination of Long Short-Term Memory (LSTM) and a Graph Attention Neural Network (GAT) to facilitate anomaly vessel trajectory warnings, ensuring precise predictions for vessel groups. Compared to prevalent algorithms like YOLO integrated with DeepSORT, our proposed method exhibits superior accuracy and captures crucial heading angle features. Importantly, it effectively mitigates the common issues of false positives and false negatives in detection and tracking tasks. Applied in the Three Rivers area of Ningbo, this research provides real-time vessel group trajectories and trajectory predictions. When the predicted trajectory suggests potential entry into a restricted zone, the system issues timely audiovisual warnings, enhancing real-time alert functionality. This framework markedly improves vessel traffic management efficiency, diminishes collision risks, and ensures secure navigation in multi-target and wide-area vessel scenarios.

Development of NIR-II small animal living fluorescence imaging system

Fluorescence imaging technology can dynamically monitor gene and cell changing in live animals in real-time, with advantages such as high sensitivity, high resolution, and non-invasion. In recent years, it has been widely used in tumor research, gene expression research, drug development research, etc. The imaging wavelength of traditional fluorescence imaging technology falls in the visible and near-infrared-I region. Due to the absorption and scattering effects of light propagation in biological tissues, and the inherent fluorescence of biological tissues, traditional fluorescence imaging techniques still have significant limitations in penetration depth and image signal-to-noise ratio. In this work, a highly integrated near-infrared-II (NIR-II, 900—1880 nm) small animal living fluorescence imaging system is developed by taking the advantages of NIR-II fluorescence imaging technology, such as low absorption, low scattering, and deep penetration depth in biological tissues. And a method of enhancing and correcting fluorescence image is proposed to optimize fluorescence images. In this work, the biological tissue simulation experiments and live animal experiments are conducted to test the performance and imaging effect of the system. The experimental results show that the system has the advantages of deep penetration depth, high signal-to-noise ratio, and high sensitivity. Combined with commercial indocyanine green reagents and aggregation-induced emission dyes, this system can monitor the distribution of blood vessels in real time and continuously monitor deep tissues and organs in mice, and conduct the dynamically monitoring research in living mice in a conscious state. This helps to promote tumor research and drug development research in the field of biomedical imaging to enter a new stage.

Application of Indian ink markers for locating gastric varices under endoscopic ultrasonography.

The present study aimed to investigate the accuracy of endoscopic ultrasonography (EUS) combined with Indian ink in locating target vessels of gastric varices (GVs) compared with conventional endoscopic techniques. Additionally, the characteristics of GVs under conventional endoscopy were also explored. All 50 cirrhotic patients with GVs between August 2021 and December 2022 were included in the study. Firstly, conventional endoscopy was employed to identify GVs and to record the expected injection sites. Subsequently, EUS was used to locate the perforated vessel and the injection site was them marked with India ink followed by injection with cyanoacrylate (CYA). Finally, conventional endoscopy was used to examine GVs, to identify the marker points of Indian ink and to compare whether the injection points under conventional endoscopy were consistent with those marked with Indian ink. Furthermore, patients with consistent and inconsistent distribution of endoscopic markers and injection sites were divided into two groups. EUS could detect the perforating vessels in real time and intuitively. The distribution of markers using EUS was significantly different compared with the injection points obtained by conventional endoscopy (P < 0.001). Therefore, 20 cases were allocated to the consistent group and 30 cases to the non-consistent group. 16 patients who showed red wale signs were obtained in the consistent group and 11 patients in the non-consistent group (P = 0.048). The diameter of the largest GVs was 13.5 (10-15) mm in the consistent group compared with 10 (7.5-10) mm in the non-consistent group (P = 0.006). EUS could provide the exact location of GVs, thus more accurately describing the endoscopic characteristics of the GVs. Furthermore, the red wale signs and diameter of the largest GVs obtained using conventional endoscopy were helpful in determining the location of target GVs.

A Real-Time Vessel Detection and Tracking System Based on LiDAR.

Vessel detection and tracking is of utmost importance to river traffic. Efficient detection and tracking technology offer an effective solution to address challenges related to river traffic safety and congestion. Traditional image-based object detection and tracking algorithms encounter issues such as target ID switching, difficulties in feature extraction, reduced robustness due to occlusion, target overlap, and changes in brightness and contrast. To detect and track vessels more accurately, a vessel detection and tracking algorithm based on the LiDAR point cloud was proposed. For vessel detection, statistical filtering algorithms were integrated into the Euclidean clustering algorithm to mitigate the effect of ripples on vessel detection. Our detection accuracy of vessels improved by 3.3% to 8.3% compared to three conventional algorithms. For vessel tracking, L-shape fitting of detected vessels can improve the efficiency of tracking, and a simple and efficient tracking algorithm is presented. By comparing three traditional tracking algorithms, an improvement in multiple object tracking accuracy (MOTA) and a reduction in ID switch times and number of missed detections were achieved. The results demonstrate that LiDAR point cloud-based vessel detection can significantly enhance the accuracy of vessel detection and tracking.

The effect of Fiber Optic RealShape technology on the reduction of radiation during complex endovascular surgery

ObjectiveDespite the advantages that fenestrated endovascular aortic repair has over open repair, it is accompanied by the consequence of radiation exposure, which can result in long-term complications for both the patient and surgical staff. Fiber Optic RealShape (FORS) technology is a novel advancement that uses emitted light from a fiber optic wire and enables the surgeon to cannulate vessels in real time without live fluoroscopy. This technology has been implemented at select centers to study its effectiveness for cannulation of target vessels and its impact on procedural radiation. MethodsWe collected prospective data on physician-modified endograft (PMEG) cases before and after the introduction of FORS technology. FORS PMEGs were matched with up to three conventional fluoroscopy cases by number of target vessels, inclusion of a bifurcated device below, aneurysm extent, and patient body mass index. The procedural radiation parameters were compared between these cohorts. Within the FORS cohort, we analyzed the rate of successful target vessel cannulation for all cases done with this technology (including cases other than PMEGs), and we compared the radiation between the cannulations using only FORS with those that abandoned FORS for conventional fluoroscopy. ResultsNineteen FORS PMEGs were able to be matched to 45 conventional fluoroscopy cases. Procedures that used FORS technology had significantly reduced total air kerma (527 mGy vs 964 mGy), dose area product (121 Gy∗cm2 vs 186 Gy∗cm2), fluoroscopy dose (72.1 Gy∗cm2 vs 132.5 Gy∗cm2), and fluoroscopy time (45 minutes vs 72 minutes). There was no difference in procedure length, total contrast, or digital subtraction angiography. Within FORS cases, 66% of cannulations were completed using only FORS. Cannulations using only FORS had significant reduction of navigation air kerma (5.0 mGy vs 26.5 mGy), dose area product (1.2 Gy∗cm2 vs 5.1 Gy∗cm2), and fluoroscopy time (0.6 minutes vs 2.3 minutes) compared with cannulations abandoning FORS for conventional fluoroscopy. ConclusionsThis study demonstrates the advantages of FORS for total procedural radiation as well as during individual cannulation tasks. The implementation of FORS for target vessel catheterization has the potential to decrease the total degree of radiation exposure for the patient and surgical staff during complex endovascular aortic surgeries.

Every Vessel Counts: Neural Network Based Maritime Traffic Counting System.

Monitoring and counting maritime traffic is important for efficient port operations and comprehensive maritime research. However, conventional systems such as the Automatic Identification System (AIS) and Vessel Traffic Services (VTS) often do not provide comprehensive data, especially for the diverse maritime traffic in Mediterranean ports. The paper proposes a real-time vessel counting system using land-based cameras is proposed for maritime traffic monitoring in ports, such as the Port of Split, Croatia. The system consists of a YOLOv4 Convolutional Neural Network (NN), trained and validated on the new SPSCD dataset, that classifies the vessels into 12 categories. Further, the Kalman tracker with Hungarian Assignment (HA) algorithm is used as a multi-target tracker. A stability assessment is proposed to complement the tracking algorithm to reduce false positives by unwanted objects (non-vessels). The evaluation results show that the system has an average counting accuracy of 97.76% and an average processing speed of 31.78 frames per second, highlighting its speed, robustness, and effectiveness. In addition, the proposed system captured 386% more maritime traffic data than conventional AIS systems, highlighting its immense potential for supporting comprehensive maritime research.

Human intravital microscopy in the study of sarcomas: an early trial of feasibility.

ClinicalTrials.gov, identifier NCT03517852; ClinicalTrials.gov, identifier NCT03823144.

Real-time monitoring and optimal vessel rescheduling in natural inland waterways

Despite the efforts made by the port community and the academia to develop Efficient strategies to mitigate the effect of unexpected events on the planning of vessels through natural waterways, most scheduling algorithms developed so far are not against these events unforseen events. These incidents may lead to nonoptimal operation or even to potentially dangerous situations. To tackle this issue, in this paper we propose a real-time monitoring architecture and a series of optimal rescheduling strategies to re-schedule vessels in real time when an unexpected incident is detected. The objective is to reduce the impact of the incident in the overall process while preserving safety. This is done by detecting deviations from the originally scheduled plans and taking the proper measures when incidents are detected, which will depend on the type of anomaly detected. The proposed methodology is applied to the case of the Guadalquivir river, a natural waterway located in the south of Spain.

Geometric Positioning Error Mitigation of SAR Image in Ocean Utilizing AIS Information

Mitigation of geometric calibration offset in ocean without utilizing ground control points was investigated in this study. Real-time AIS information on vessels was exploited after preprocessing and accordingly tested against the detected vessels in the SAR image. Repetitive procedure of measuring the offset between the AIS sensor and the vessel detection was conducted and derived the SAR image of which the positioning offset was ameliorated. The proposed geo-location enhancement algorithm demonstrated the possibility of application in real-time vessel monitoring from remote sensing.

Robotic real-time vessel navigation using indocyanine green fluorescence for lymph node dissection along the left gastroepiploic vessels during robotic distal gastrectomy - First experience.

Splenic infarction (SI) following gastrectomy is common; severe complications related to SI, such as splenic haemorrhage, abscess formation or rupture, can be fatal. To overcome these problems, we performed real-time vessel navigation using indocyanine green (ICG) fluorescence during robotic distal gastrectomy (RDG). The aim of study is to report the efficacy of robotic real-time vessel navigation for lymph node dissection (LND) along left gastroepiploic vessels (LGEVs). We treated seven patients with gastric cancer who underwent LND along the LGEVs using robotic real-time vessel navigation during RDG at our institution from January 2021 to July 2021. There were no complications (Clavien-Dindo classification II). There were no cases of post-operative SI or spleen-related complications. Robotic real-time vessel navigation using ICG for LND along LGEVs during RDG could help to reduce post-operative spleen-related complications associated with RDG.

A Clustering-based Approach for Predicting the Future Location of a Vessel

In recent years the number of vessel accidents has increased with the growing number of vessels in the Ocean. A substantial number of these accidents are due to human errors. However, a vessel could avoid some accidents if it knows future locations or trajectories of surrounding vessels. The future location (or trajectory) prediction of vessels is also valuable for maritime traffic management and planning. Existing approaches for predicting the future location are not vessel-specific, but the behavioural pattern of each type of vessel is different. On the other hand, clustering-based approaches are computationally expensive due to computing the similarity measures among vessel trajectories. In this paper, we propose a clustering-based framework that consists of three modules: dataset preparation, route clustering, and location prediction model. The main novelty of this proposal is that the prediction models are built using only trajectories of vessels of the same type, which we hypothesise will increase their accuracy. The other main contribution of our work is the evaluation of different strategies to improve computational efficiency, which can be critical for real-time vessel location prediction. We have used a density-based hierarchical clustering algorithm, HDBSCAN, where two fast implementations of trajectory similarity measures (Hausdorff Distance and Dynamic Time Warping) are evaluated for clustering route patterns. Also, the effect of using a trajectory compression algorithm (Ramer–Douglas–Peucker) to expedite the clustering process is analyzed. The performance of our approach is evaluated using real-world AIS data. We have compared our proposal against two baseline models. Evaluation results confirm the validity of the proposed approach for prediction of the future location of vessels

Real-time vessel segmentation and reconstruction for virtual fixtures for an active handheld microneurosurgical instrument.

Complications related to vascular damage such as intra-operative bleeding may be avoided during neurosurgical procedures such as petroclival meningioma surgery. To address this and improve the patient's safety, we designed a real-time blood vessel avoidance strategy that enables operation on deformable tissue during petroclival meningioma surgery using Micron, a handheld surgical robotic tool. We integrated real-time intra-operative blood vessel segmentation of brain vasculature using deep learning, with a 3D reconstruction algorithm to obtain the vessel point cloud in real time. We then implemented a virtual-fixture-based strategy that prevented Micron's tooltip from entering a forbidden region around the vessel, thus avoiding damage to it. We achieved a median Dice similarity coefficient of 0.97, 0.86, 0.87 and 0.77 on datasets of phantom blood vessels, petrosal vein, internal carotid artery and superficial vessels, respectively. We conducted trials with deformable clay vessel phantoms, keeping the forbidden region 400 [Formula: see text]m outside and 400 [Formula: see text]m inside the vessel. Micron's tip entered the forbidden region with a median penetration of just 8.84 [Formula: see text]m and 9.63 [Formula: see text]m, compared to 148.74 [Formula: see text]m and 117.17 [Formula: see text]m without our strategy, for the former and latter trials, respectively. Real-time control of Micron was achieved at 33.3 fps. We achieved improvements in real-time segmentation of brain vasculature from intra-operative images and showed that our approach works even on non-stationary vessel phantoms. The results suggest that by enabling precise, real-time control, we are one step closer to using Micron in real neurosurgical procedures.

Noninvasive Pressure Estimation Based on the Subharmonic Response of SonoVue: Application to Intracranial Blood Pressure Assessment.

Intracranial blood pressure can directly reflect the status of blood vessels in real time. However, it can only be estimated invasively using a microcatheter during craniotomy. Subharmonic-aided pressure estimation (SHAPE) is a promising technique for estimating cardiac pressures but mainly uses Sonazoid, whereas SHAPE using SonoVue is still in the early stages of development. The aim of this study was to optimize transcranial SHAPE using SonoVue by investigating the relationship between subharmonic signals and middle cerebral artery pressure (MCAP) (20-160 mmHg) in vitro. We examined the effect of acoustic output levels (peak negative pressures (PNPs) of 238, 346, and 454 kPa), time in suspension (time from reconstituting the suspension to extracting it: 0-30 min), and exposure to gas-equilibrated saline (3 min, 1 h, or original gas completely replaced by air) on the subharmonic-pressure relationship. A mean subharmonic amplitude over a 0.4 MHz bandwidth was extracted using a 5 MHz 12-cycle pulse. A PNP of 346 kPa elicited the best subharmonic sensitivity for assessing hydrostatic pressures up to 0.24 dB/mmHg, possibly because compression-only behavior no longer occurs at this pressure. Moreover, the expansion force is not large enough to offset the effects of hydrostatic pressure. A linear monotonic relationship between the subharmonic amplitude and hydrostatic pressure was only observed for just prepared SonoVue. Excessive exposure to gas-equilibrated saline also affected the subharmonic-pressure relationship. Therefore, just prepared SonoVue should be used, and the duration of the pressure estimation process should be strictly controlled.

A new orchiopexy in lateral position for intraabdominal testis―One-staged laparoscopic testicular artery and gubernaculum sparing orchiopexy through inguinal canal using real-time vessel navigation with indocyanine green fluorescence to evaluate blood flow of testicular artery

A new orchiopexy in lateral position for intraabdominal testis―One-staged laparoscopic testicular artery and gubernaculum sparing orchiopexy through inguinal canal using real-time vessel navigation with indocyanine green fluorescence to evaluate blood flow of testicular artery

Intraosseus access vs ecoguided peripherical venous access in emergency and urgency: a systematic review.

Ensuring vascular access in emergency conditions is critical. Peripheral venous catheters (CVP) are the most used devices in clinical practice, even though their positioning can result difficult, causing delay in life-support treatments with possible critical results. Ultrasounds allow you to view blood vessel in real time, for this reason they could result helpful during use. Another option for the vascular access can be intraosseous access (I.O.), by introducing a needle directly in the bone marrow cavity. This review aim is to examine what typology of vascular access is best for the drug delivery in emergency/urgency in international and national literature. Bibliographical research was conducted by consulting the main biomedical databases through keywords and MESH terminology. In this review 21 articles published in the last 7 years have been included. They were published in English, Italian and French. Contraindications and complications of I.O and of ultrasound-guided CVP positioning are limited. I.O access finding attempts are as fast as CVP positioning attempts but with a higher chance of success. Furthermore, ultrasound-guided CVP insertion is more comfortable for patients, it minimizes delays in medical treatment and it guarantees a better healthcare, with high percentage of right venous catheter placement. Intraosseous access is recommended for severely compromised patients; the ultrasound guide is a very useful tool when peripheral vascular areas are difficult to detect with only the palpation, it would be more appropriate in situations of urgency than that of emergency.