High Definition Research Articles

SURG-35. NEURONAVIGATED INTRAOPERATIVE ULTRASSOUND X SODIUM FLUORESCEIN FOR BRAIN METASTASIS: WHICH IS BETTER?

Abstract BACKGROUND Improve quality of life with a maximum surgical resection is the main goal of neurosurgeons. Brain metastasis are even more prevalent because of patients are living more. The grade of resection and the maintenance of a good performance are fundamental for these patients perform adjuvant radiotherapy. There are several technologies that may help. Considering two of them that have an easier access and are cheaper, we compared a high definition ultrasound (BK 3000) coupled to neuronavigation system (Brainlab) and sodium fluorescein (SF). METHODS Adult patients with main radiological hypothesis of brain metastasis were included in a PhD study previously approved by ethics committee. 3-5mg/kg of SF was administered by intravenous infusion during anesthetic induction. An specific craniotomy transducer was used in all cases with shift correction in real time by neuronavigator. All procedures were guided by the same neurosurgeon. RESULTS High definition ultrasound allows an excellent tumor delimitation. SF helped to increase grade of resection however made confusion about what is infiltration and what is tumor and for this ultrasound were superior. Increased fluorescence is easily detected when compared to ultrasound information’s.. For both technologies, when the surgical site had blood, the evaluation about grade of resection is not accurate because in ultrasound appears a posterior shadow and considering SF it seems that there are not further tumor because blood does not have increased fluorescence. CONCLUSIONS US and SF are different tools which improve brain metastasis resection. In each moment of surgery one technology was superior or not. We used an specific probe for neurosurgery that has high quality and allowed detailed evaluations. These technologies helps surgeons take quick decision and optimized brain tumor removal. The neurosurgeon should be more familiar to US images because provide a real time evaluation with low cost.

SURG-33. INTRAOPERATIVE ULTRASSOUND X SODIUM FLUORESCEIN FOR GLIOMA SURGERY: WHICH IS BETTER?

Abstract BACKGROUND Improve quality of life with a maximum surgical resection is the main goal of neurosurgeons. A better delimitation of intrinsic brain tumors are required for achieving a maximum tumor removal. There are several technologies that may help. Considering two of them that have an easier access and are cheaper, we compared a high definition ultrasound (BK 3000) and sodium fluorescein (SF) during glioma surgeries. METHODS Adult patients with main radiological hypothesis of low or high grade glioma were included in a PhD study previously approved by ethics committee. 3-5mg/kg of SF was administered by intravenous infusion during anesthetic induction. An specific craniotomy transducer was used in all cases. All procedures were guided by the same neurosurgeon. RESULTS High definition ultrasound allows an excellent tumor delimitation in high and low grade tumors. However the gray scale and distinction of brain structures and residual lesion was difficult for surgeons who are not habituated to ultrasound use. SF did not help low grade glioma removal, and in these cases ultrasound were superior. Increased fluorescence is easily detected when compared to ultrasound information’s. For small residual tumor, SF helps more than US. For both technologies, when the surgical site had blood, the evaluation about grade of resection is not accurate because in ultrasound appears a posterior shadow and considering SF it seems that there are not further tumor because blood does not have increased fluorescence. CONCLUSIONS US showed superiority for low grade gliomas resection. Considering high grade, both technologies helps in different moments during the surgery and are complimentary. We used an specific probe for neurosurgery that has high quality and allowed detailed evaluations. These technologies helps surgeons take quick decision and optimized brain tumor removal. The neurosurgeon should be more familiar to US images because provide a real time evaluation with low cost. KEY WORDS: ultrasound; fluorescein; gliomas; brain tumors

High definition 3D models of small legume seed: a close up application to support ancient plant genomics

Abstract. Legume seeds are essential for nutrition and play crucial roles in food security, climate change mitigation, biodiversity conservation, and sustainability. Among them, the common bean (Phaseolus vulgaris L.) is the most widely cultivated and vital to the food value chain. Originating in Mesoamerica and independently domesticated there and in the Andes about 8,000 years ago, common beans have adapted to diverse environments globally following the Columbian exchange. Ancient DNA (aDNA) sequencing offers insights into the bean’s adaptation and evolution, but traditional methods struggle with detailed 3D phenotypic analysis due to the beans’ small size and the destructive nature of aDNA extraction. Expensive high-detail optical instruments are not commonly available in genetic labs. This research proposes macro-photogrammetry as a low-cost technique for creating detailed 3D digital replicas of beans. By using samples from archaeological sites in northern Peru, this method preserves phenotypic information despite the destruction of physical samples during DNA extraction. The study details the process of capturing high-detail images with specialized equipment to build a digital phenotype library, preserving the morphological features of ancient beans for further study and future comparison with modern varieties.

Improved automated parallel implementation of GMM background subtraction on a multicore digital signal processor

<p><span>Scene segmentation is an essential step in a wide range of video processing applications, for instance, object recognition and tracking. The Gaussian mixture model (GMM) for background subtraction (BS) has gained widespread usage in scene segmentation, despite its known computational intensity. To tackle this challenge, we propose a practical solution to accelerate processing through a parallel implementation on an embedded multicore platform. In this paper, we present an improved automated parallel implementation of the GMM algorithm using the Orphan directive provided by open multiprocessing (OpenMP). Experimental assessments conducted on the eight cores of the C6678 digital signal processor (DSP) demonstrate significant advancements in parallel efficiency, particularly when handling high-resolution frames, including high-definition (HD) and full-HD resolutions. The achieved parallel efficiency surpasses the results obtained with classical OpenMP scheduling modes, encompassing dynamic, static, and guided approaches. Specifically, the parallel efficiency reaches approximately 82% for full-HD resolution frames and, 99.3% for low-resolution frames, respectively.</span></p>

A Base-Map-Guided Global Localization Solution for Heterogeneous Robots Using a Co-View Context Descriptor

With the continuous advancement of autonomous driving technology, an increasing number of high-definition (HD) maps have been generated and stored in geospatial databases. These HD maps can provide strong localization support for mobile robots equipped with light detection and ranging (LiDAR) sensors. However, the global localization of heterogeneous robots under complex environments remains challenging. Most of the existing point cloud global localization methods perform poorly due to the different perspective views of heterogeneous robots. Leveraging existing HD maps, this paper proposes a base-map-guided heterogeneous robots localization solution. A novel co-view context descriptor with rotational invariance is developed to represent the characteristics of heterogeneous point clouds in a unified manner. The pre-set base map is divided into virtual scans, each of which generates a candidate co-view context descriptor. These descriptors are assigned to robots before operations. By matching the query co-view context descriptors of a working robot with the assigned candidate descriptors, the coarse localization is achieved. Finally, the refined localization is done through point cloud registration. The proposed solution can be applied to both single-robot and multi-robot global localization scenarios, especially when communication is impaired. The heterogeneous datasets used for the experiments cover both indoor and outdoor scenarios, utilizing various scanning modes. The average rotation and translation errors are within 1° and 0.30 m, indicating the proposed solution can provide reliable localization support despite communication failures, even across heterogeneous robots.

Cloud IaaS Optimization Using Machine Vision at the IoT Edge and the Grid Sensing Algorithm.

Security grids consisting of High-Definition (HD) Internet of Things (IoT) cameras are gaining popularity for organizational perimeter surveillance and security monitoring. Transmitting HD video data to cloud infrastructure requires high bandwidth and more storage space than text, audio, and image data. It becomes more challenging for large-scale organizations with massive security grids to minimize cloud network bandwidth and storage costs. This paper presents an application of Machine Vision at the IoT Edge (Mez) technology in association with a novel Grid Sensing (GRS) algorithm to optimize cloud Infrastructure as a Service (IaaS) resource allocation, leading to cost minimization. Experimental results demonstrated a 31.29% reduction in bandwidth and a 22.43% reduction in storage requirements. The Mez technology offers a network latency feedback module with knobs for transforming video frames to adjust to the latency sensitivity. The association of the GRS algorithm introduces its compatibility in the IoT camera-driven security grid by automatically ranking the existing bandwidth requirements by different IoT nodes. As a result, the proposed system minimizes the entire grid's throughput, contributing to significant cloud resource optimization.

High-Definition Trans-Spinal Current Stimulation Improves Balance and Somatosensory Control: A Randomised, Placebo-Controlled Trial.

To investigate and compare the effects of three different high-definition (HD) non-invasive current stimulation (NICS) protocols on the spinal cord on support balance and somatosensory abilities in healthy young people. Fifty-eight students were enrolled in this crossover study. All participants underwent application of (i) 1.5 mA anodal high-definition trans spinal direct current stimulation (HD-tsDCS), (ii) 1.5 mA cathodal HD-tsDCS, (iii) 1.5 mA high-definition trans spinal alternating current stimulation (HD-tsACS), and (iv) sham HD-tsDCS/ACS over the eighth thoracic vertebra in a randomised order. Balance (Y Balance test), deep sensitivity (Tuning Fork Test), and superficial sensitivity (Monofilament Test) of the lower limbs were tested immediately before and after each intervention. Balance ability improved significantly following anodal HD-tsDCS and HD-tsACS compared with that following sham HD-tsDCS/ACS. Similarly, deep sensitivity increased significantly with anodal HD-tsDCS and HD-tsACS compared to that with sham HD-tsDCS/ACS and cathodal HD-tsDCS. Furthermore, superficial sensitivity improved significantly following anodal HD-tsDCS compared with that after HD-tsACS and cathodal HD-tsDCS. Our data show that HD-tsNICS effectively modulates the balance and somatosensory control of the lower limbs. Several diseases are associated with illness-induced changes in the spinal network in parallel with sensorimotor disabilities. Non-invasive spinal modulation may be a favourable alternative to conventional brain applications in rehabilitation. Future studies should therefore investigate these promising approaches among cohorts of patients with disabilities.

Organizing planning knowledge for automated vehicles and intelligent transportation systems

AbstractIntelligent Transportation Systems (ITS) are crucial for developing fully automated vehicles. While significant progress has been made with advanced driver assistance systems and automation technology, challenges remain, such as improving traffic information, enhancing planning and control systems, and developing better decision‐making capabilities. Despite these hurdles, the potential benefits of ITS are so many that its challenges have attracted substantial industrial investment and research groups interested in the automated driving field. In this work, a methodology based on state space search for planning knowledge integration is proposed. The main goal of the proposal is to provide a planning system with the necessary information to perform properly any task related to lateral and longitudinal control, path following, trajectory generation, arbitration and behavior execution by localizing the vehicle with respect to a high‐level road plan. To this end, this research compares cutting‐edge methods for rapidly finding the K nearest neighbor in relatively high dimensional road plans constructed from the traffic information stored in a high definition map. During the experimentation phase, promising real‐time results have been obtained for fast KNN algorithms, leading to a robust tree index‐based methodology for decision making in self‐driving vehicles combining path planning, trajectory tracking, trajectory creation, knowledge aggregation and precise vehicle control.

Diagnosis and Analysis of Vasa Previa Types With Flow HD Glass Body.

To explore the value of applying flow high definition (HD) glass body in prenatal diagnosis of vasa previa and to preliminarily discuss the types of vasa previa. Two-dimensional ultrasound, flow HD, and flow HD glass body were used to image the umbilical cord insertion site and placenta, observe the cervical internal os and surrounding areas, and retrospectively analyze cases of vasa previa. There were 15 cases of vasa previa, including 14 cases of singleton pregnancies and 1 case of twin pregnancy, with a total of 22 vasa previa, including 10 veins and 12 arteries. There was 1 case with 3 vessels, 5 cases with 2 vessels, and 9 cases with a single vessel. Among them, in 3 cases of vasa previa detected at 12, 14, and 24 weeks, respectively, the vasa previa were relocated to a normal position at 24, 29, and 35 weeks of gestation when re-examined. Routine 2-dimensional ultrasound examination in this group showed tubular or circular hypoechoic areas near the cervical internal os, but vasa previa could not be confirmed. Flow HD could display color blood flow at and near the cervical internal os in 15 cases, but it was difficult to continuously show the course and source of the blood vessels under the chorion. Flow HD glass body from multiple angles could display the relationship between 15 cases of 22 vasa previa and the placenta and cervix. Combined with color Doppler blood flow spectra, flow HD glass body could determine the types of vasa previa. Flow HD glass body imaging can clearly display vasa previa, showing their origin and the spatial relationship with the cervix and placenta in a 3-dimensional manner, displaying the course and attachment points of umbilical vessels under the chorion. It can observe the area of interest at any angle, and combined with color Doppler blood flow spectra, it can judge the vasa previa of the umbilical vein, providing a more definite imaging basis for clinical management.

Interest HD: An Interest Frame Model for Recommendation Based on HD Image Generation.

This work is inspired by high-definition (HD) image generation techniques. When the user's interests are viewed as different frames of varying clarity, the unclear parts of one interest frame can be clarified by other interest frames. The user's overall HD interest portrait can be viewed as a fusion of multiple interest frames through detail compensation. Based on this inspiration, we propose a model for generating HD interest portrait called interest frame for recommendation (IF4Rec). First, we present a fine-grained pixel-level user interest mining method, Pixel embedding (PE) uses positional coding techniques to mine atomic-level interest pixel matrices in multiple dimensions, such as time, space, and frequency. Then, using an atomic-level interest pixel matrix, we propose Item2Frame to generate several interest frames for a user. The similarity score of each item is calculated to fill the multi-interest pixel clusters, through an improved self-attention mechanism. Finally, stimulated by HD image generation techniques, we initially present an interest frame noise compensation method. By utilizing the multihead attention mechanism, pixel-level optimization and noise complementation are performed between multi-interest frames, and an HD interest portrait is achieved. Experiments show that our model mines users' interests well. On five publicly available datasets, our model outperforms the baselines.

Microbial laden mobile phones from international conference attendees pose potential risks to public health and biosecurity

IntroductionMobile phones, contaminated with pathogenic microorganisms, have the potential to act as “trojan horses”. The microbial signatures present on their surfaces most probably vary across different geographical regions. As a result, mobile phones belonging to international conference attendees may serve as a model for global microbial dissemination, posing potential risks to public health and biosecurity. AimThis study aimed to profile the microbes present on mobile phones belonging to delegates attending an international scientific conference through use of metagenomic shotgun DNA sequencing. MethodsTwenty mobile phones, representing ten different geographical zones from around the world, were swabbed and pooled together into ten geographical-specific samples for high definition next-generation DNA sequencing. WONCA council members were invited to participate and provided verbal consent. Following DNA extraction, next generation sequencing, to a depth of approximately 10Gbp per sample, was undertaken on a v1.5 Illumina NovaSeq6000 system. Bioinformatic analysis was performed via the CosmosID platform. ResultsA total of 2204 microbial hits were accumulated across 20 mobile phones inclusive of 882 bacteria, 1229 viruses, 88 fungi and 5 protozoa. Of particular concern was the identification of 65 distinct antibiotic resistance genes and 86 virulence genes. Plant, animal and human pathogens, including ESKAPE and HACEK bacteria were found on mobile phones. Discussion/conclusionMobile phones of international attendees are contaminated with many & varied microorganisms. Further research is required to characterize the risks these devices pose for biosecurity and public health. Development of new policies which appropriately address and prevent such risks maybe warranted.

Molecular and spatial transcriptomic classification of midbrain dopamine neurons and their alterations in a LRRK2G2019S model of Parkinson's disease.

Several studies have revealed that midbrain dopamine (DA) neurons, even within a single neuroanatomical area, display heterogeneous properties. In parallel, studies using single cell profiling techniques have begun to cluster DA neurons into subtypes based on their molecular signatures. Recent work has shown that molecularly defined DA subtypes within the substantia nigra (SNc) display distinctive anatomic and functional properties, and differential vulnerability in Parkinson's disease (PD). Based on these provocative results, a granular understanding of these putative subtypes and their alterations in PD models, is imperative. We developed an optimized pipeline for single-nuclear RNA sequencing (snRNA-seq) and generated a high-resolution hierarchically organized map revealing 20 molecularly distinct DA neuron subtypes belonging to three main families. We integrated this data with spatial MERFISH technology to map, with high definition, the location of these subtypes in the mouse midbrain, revealing heterogeneity even within neuroanatomical sub-structures. Finally, we demonstrate that in the preclinical LRRK2G2019S knock-in mouse model of PD, subtype organization and proportions are preserved. Transcriptional alterations occur in many subtypes including those localized to the ventral tier SNc, where differential expression is observed in synaptic pathways, which might account for previously described DA release deficits in this model. Our work provides an advancement of current taxonomic schemes of the mouse midbrain DA neuron subtypes, a high-resolution view of their spatial locations, and their alterations in a prodromal mouse model of PD.

Global Localization using OpenStreetMap and Elevation Offsets

Localization is a critical component in autonomous vehicle navigation stacks. While GNSS-only localization cannot be fully reliable and available all the time, localization based on 3D high-definition (HD) maps have to be robust to world changes, which is still a challenging issue. Added to that, in general, HD maps are expensive and difficult to construct and maintain.In this paper, we propose a particle filter-based 2D global pose estimation method that can use the crowdsourced OpenStreetMap (OSM) API, a digital surface map, or both. The main contributions of the proposed approach are: that it is lightweight, does not require the vehicle to map the environment, does not require a GPU (can be used with low-power computing resources), is agnostic to the odometry source, and achieved relatively low position and orientation errors for this localization modality using the KITTI dataset sequences. The proposed method's implementation is open source and is available with the experimental results on our GitHub page.

Radical Interpretations of Iconic works for Percussion

The artistic development project Radical Interpretations investigates two iconic works for solo percussion and re-composes these. The goal of the project was to develop new creative and transdisciplinary research in interpretation of musical works. Participants: percussionist Kjell Tore Innervik, Norwegian Academy of Music (NMH), composer Ivar Frounberg, NMH, designer Maziar Raein, Oslo National Academy of the Arts, experience designer Ståle Stenslie, The Oslo School of Architecture and Design, and music recording producer Morten Lindberg. During the 3 years project, the team engaged with the music of Morton Feldman and Iannis Xenakis. The solo percussion pieces The King of Denmark and Psappha were the point of departure. The cd [UTOPIAS ](http://www.2l.no/pages/album/141.html)(2L) contains the pure audio version of the pieces in high definition and immersive sound.-><- On this site you will find other interpretations and iterations of the music made by the team.

Vehicle Localization Using Crowdsourced Data Collected on Urban Roads.

Vehicle localization using mounted sensors is an essential technology for various applications, including autonomous vehicles and road mapping. Achieving high positioning accuracy through the fusion of low-cost sensors is a topic of considerable interest. Recently, applications based on crowdsourced data from a large number of vehicles have received significant attention. Equipping standard vehicles with low-cost onboard sensors offers the advantage of collecting data from multiple drives over extensive road networks at a low operational cost. These vehicle trajectories and road observations can be utilized for traffic surveys, road inspections, and mapping. However, data obtained from low-cost devices are likely to be highly inaccurate. On urban roads, unlike highways, complex road structures and GNSS signal obstructions caused by buildings are common. This study proposes a reliable vehicle localization method using a large amount of crowdsourced data collected from urban roads. The proposed localization method is designed with consideration for the high inaccuracy of the data, the complexity of road structures, and the partial use of high-definition (HD) maps that account for environmental changes. The high inaccuracy of sensor data affects the reliability of localization. Therefore, the proposed method includes a reliability assessment of the localized vehicle poses. The performance of the proposed method was evaluated using data collected from buses operating in Seoul, Korea. The data used for the evaluation were collected 18 months after the creation of the HD maps.

RETNet: Resolution enhancement Transformer network for magnetic particle imaging based on X-space

Magnetic Particle Imaging (MPI) can visualize the concentration distribution of superparamagnetic iron-oxide nanoparticles (SPIONs) in tissues with the advantages of high sensitivity and high temporal resolution. However, the low spatial resolution of MPI limits its application. Increasing the gradient strength of the selection field can improve the resolution of MPI, but also increase power consumption and noise. A feasible and cost-effective method to address this limitation is to reconstruct high gradient (HG) image from low gradient (LG) image using algorithms. Deep learning has been a powerful tool for improving the resolution of medical imaging techniques. In this study, we propose a Resolution Enhancement Transformer Network (RETNet) for reconstructing HG image with high-resolution from LG image with low-resolution as input, avoiding high power consumption and high noise in the system with HG field. RETNet leverages a shallow feature extractor to capture shallow features, a cross-scale-Transformer (CST) to focus on textural features, a residual-swin-Transformer (RST) to focus on structural features, and an image reconstruction module to aggregate these three types of features and reconstruct the HG image. Textural and structural features extracted can ensure the integrity of the details and the realization of high definition in the reconstructed image. Ablation experiments demonstrate the significant contribution of these two modules to reconstruct the HG image. Comparative experiments, including experiments at noise-free and multiple noise levels, confirm the high robustness of RETNet. Simulation, phantom, and in vivo experiments consistently demonstrate that RETNet outperforms competing methods and effectively improves the resolution of MPI.

Heliostat geometrical characterization by UAV-assisted, close-range photogrammetry

An innovative approach for the characterization of the mirror geometry of Concentrating Solar Thermal (CST) plants is presented in this article. The approach takes advantage of the current advances in the commercial unmanned aerial vehicle (UAV) technology to perform airborne, close-range photogrammetry for accurate characterization of the mirror’s geometry. To improve spatial resolution and, thus, reconstruction performance, the approach involves a projector for projecting a feature-rich image on the surface of the mirror to be characterized. A UAV flying on a predetermined flight path is used to capture overlapping snapshots of the projected image using its on-board high definition digital camera. By the use of photogrammetry tools, the snapshots are stitched together and processed accordingly to reconstruct the surface of the reflector. Although the approach was tested and validated experimentally by characterizing the mirror surface of a single-facet heliostat, the developed method can also be applied for the characterization of any type of solar concentrating mirror geometry.

Ability of detection in different resolution endoscopy for upper gastrointestinal mucosal lesions

BackgroundMost endoscopists believe that higher resolution improves lesion detection rates. However, existing studies primarily compared the detection rates of white light endoscopy (WLE) and other imaging modalities. Our previous study demonstrated the advantages of magnifying endoscopy from general endoscopy for lesion detection, prompting further investigation into the variations in lesion detection rates across endoscopes with different resolutions.MethodsEndoscopic and corresponding pathological data from our medical unit over the past 5 years were analyzed. We excluded specific-purpose endoscopic procedures to ensure the natural randomization of the data. Baseline adjustment and risk factor analyses used multi-group propensity score matching and logistic regression.ResultsThe overall lesion detection rate was significantly higher with high-quality endoscopy (Q-endoscopy) compared to high-definition endoscopy (H-endoscopy) and high definition and quality endoscopy (HQ-endoscopy) (34.4% vs. 30.2% vs. 29.6%, P = 0.001). Similar results were observed for elevated lesions (25.7% vs. 21.0% vs. 22.9%, P = 0.001) and depressed lesions (6.6% vs. 6.2% vs. 3.6%, P < 0.001). HQ-endoscopy had a superior detection rate for superficial lesions compared to both H- and Q-endoscopies (3.0% vs. 2.8% vs. 1.8%, P = 0.041). However, there were no significant differences in neoplastic detection rate or missed neoplastic lesion rate among the three groups.ConclusionQ-endoscopy is superior in detecting non-superficial lesions, while HQ-endoscopy is better at detecting superficial lesions. However, there were no statistically significant differences in detecting or omitting neoplastic lesions among the three endoscopic examinations.

The staining results of early gastric cancer by indigo carmine chromoendoscopy associated with histological structure: a retrospective study

BackgroundAt present, conventional endoscopy and chromoendoscopy using indigo carmine (IC) is a very useful method to determine the demarcation line (DL) of early gastric cancer lesions, but it is not suitable for all lesions.AimsThis study aimed to determine the applicable conditions for IC chromoendoscopy.MethodsWe retrospectively evaluated 187 lesions in 181 patients who had an endoscopic diagnosis of EGC and were treated with endoscopic submucosal dissection (ESD). According to the existence of the DL between the lesion mucosa and normal mucosa with IC chromoendoscopy, the lesions were divided into two groups: clear group and unclear group. Clinicopathological characteristics were evaluated in each group. From January 2022 to March 2023, the postoperative pathological sections of 19 lesions (81 slices) in the clear group and 19 lesions (80 slices) in unclear group were scanned with high definition, and the crypt structure between the two groups was evaluated.ResultsThere was no significant difference in clinical factors between the clear group and unclear group. There were significant differences in crypt area, crypt length, and crypt opening diameter between the two groups. In the clear group, there were significant differences in crypt area, crypt length, and crypt opening diameter between the normal area and cancer area, but there was no significant difference in the unclear group.ConclusionsThe margins of lesions with fused or absent crypt structures, a small crypt area, a short crypt length, and a short crypt opening diameter can be easily determined with IC chromoendoscopy.

An Object-Centric Hierarchical Pose Estimation Method Using Semantic High-Definition Maps for General Autonomous Driving.

To achieve Level 4 and above autonomous driving, a robust and stable autonomous driving system is essential to adapt to various environmental changes. This paper aims to perform vehicle pose estimation, a crucial element in forming autonomous driving systems, more universally and robustly. The prevalent method for vehicle pose estimation in autonomous driving systems relies on Real-Time Kinematic (RTK) sensor data, ensuring accurate location acquisition. However, due to the characteristics of RTK sensors, precise positioning is challenging or impossible in indoor spaces or areas with signal interference, leading to inaccurate pose estimation and hindering autonomous driving in such scenarios. This paper proposes a method to overcome these challenges by leveraging objects registered in a high-precision map. The proposed approach involves creating a semantic high-definition (HD) map with added objects, forming object-centric features, recognizing locations using these features, and accurately estimating the vehicle's pose from the recognized location. This proposed method enhances the precision of vehicle pose estimation in environments where acquiring RTK sensor data is challenging, enabling more robust and stable autonomous driving. The paper demonstrates the proposed method's effectiveness through simulation and real-world experiments, showcasing its capability for more precise pose estimation.