2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)最新文献

Accuracy of position and orientation for consumer-grade tracking sensors with Hand-Eye Calibration 使用手眼校准的消费级跟踪传感器的位置和方向精度

2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2023-06-14 DOI: 10.1109/MeMeA57477.2023.10171956

Ilaria Mileti, F. Patané

{"title":"Accuracy of position and orientation for consumer-grade tracking sensors with Hand-Eye Calibration","authors":"Ilaria Mileti, F. Patané","doi":"10.1109/MeMeA57477.2023.10171956","DOIUrl":"https://doi.org/10.1109/MeMeA57477.2023.10171956","url":null,"abstract":"Extrinsic calibration of motion tracking sensors is a fundamental aspect for the design and development of wearable measurement system and robotics devices. In this study, we evaluated the accuracy of consumer-grade tracking sensors, implementing a linear hand-eye algorithm, in order to minimize the systematic effect of sensor-to-frame misalignment. Three consumer-grade tracking sensors were used in this study, an Inertial Odometry-Vision system, a VR-device based on infrared (IR) structured light, and an Inertial Measurement Unit. The three systems were placed on the end-effector of an industrial robot UR5e, whose trajectories and rotations were taken as reference. The hand-eye-calibration method was applied to estimate the actual alignment of the sensor’ frames in respect to the end-effector one. The experimental protocol was conducted considering a set of 16 calibration trials, with two joint speeds: (i) 30°/s (acceleration 30°/s) and (ii) 15° (acceleration 15°/s). Each run had a time duration of 3 min. The 8 low-speed trials were characterized by a reproducibility of ±1°, ±1.2° and ±1.8°, for the three sensors, respectively. The beneficial effect of calibration resulted significant only for the Inertial Measurement Unit, with an inaccuracy reduction of 2°. No significant improvement in the accuracy of the other sensors was observed for either orientation or position tracking. The results suggest that for applications where a precise alignment among sensors is required, the accuracy of consumer-grade tracking sensors may be not sufficient, even implementing an optimal calibration procedure, in particular for Inertial Measurement Units.","PeriodicalId":191927,"journal":{"name":"2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116678340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prostate cancer risk assessment using a radiogenomic analysis 使用放射基因组分析进行前列腺癌风险评估

2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2023-06-14 DOI: 10.1109/MeMeA57477.2023.10171915

C. D. Fernandes, Annekoos Schaap, Joan Kant, Petra J. van Houdt, H. Wijkstra, U. A. Heide, W. Zwart, M. Mischi, F. Eduati, S. Turco

{"title":"Prostate cancer risk assessment using a radiogenomic analysis","authors":"C. D. Fernandes, Annekoos Schaap, Joan Kant, Petra J. van Houdt, H. Wijkstra, U. A. Heide, W. Zwart, M. Mischi, F. Eduati, S. Turco","doi":"10.1109/MeMeA57477.2023.10171915","DOIUrl":"https://doi.org/10.1109/MeMeA57477.2023.10171915","url":null,"abstract":"Prostate cancer (PCa) is a very prevalent cancer type with a heterogeneous prognosis. An accurate assessment of tumor aggressiveness can pave the way for tailored treatment strategies, potentially leading to a better prognosis. Tumor aggressiveness is typically assessed based on invasive methods (e.g. biopsy), but combining diagnostic imaging with genomic information can help uncover aggressive (imaging) phenotypes, which can provide non-invasive advice on individualized treatment regimens. In this study, we aim to identify relevant tumor imaging features from diagnostic multi-parametric MRI sequences, which can then be related to the underlying genomic information derived based on RNA sequencing data. To isolate relevant imaging features that can represent the underlying tumor phenotype, different machine learning models (support vector machine [SVM], k-nearest neighbors [KNN], and logistic regression [LR]) were trained and optimized to classify tumors in either clinically insignificant or significant PCa, based on their Gleason score. These models were trained and validated in two independent cohorts consisting of 45 and 35 patients, respectively. An LR model obtained the highest performance in the validation dataset with a balanced accuracy = 73%, sensitivity = 54%, and specificity = 91%. Significant correlations were found between the identified perfusion-based imaging features and genomic features, highlighting a relationship between imaging characteristics and the underlying genomic information.","PeriodicalId":191927,"journal":{"name":"2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121032453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Statistical Analysis of Multispectral NIR Images for Vein Detection 多光谱近红外图像用于静脉检测的统计分析

2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2023-06-14 DOI: 10.1109/MeMeA57477.2023.10171947

J. Dave, Sneha Chand, GS Rahul, Antony Raj, S. Preejith, M. Sivaprakasam

{"title":"Statistical Analysis of Multispectral NIR Images for Vein Detection","authors":"J. Dave, Sneha Chand, GS Rahul, Antony Raj, S. Preejith, M. Sivaprakasam","doi":"10.1109/MeMeA57477.2023.10171947","DOIUrl":"https://doi.org/10.1109/MeMeA57477.2023.10171947","url":null,"abstract":"Vein localization is crucial for successful cannulation, but it can be challenging due to factors such as skin colour and Body Mass Index (BMI). While near-infrared (NIR) imaging is established for improving vein visibility, the optimal wavelength for patients with varying skin colours and BMIs has not been thoroughly studied. Thus, it is important to explore optimal wavelength selection to address these influencing factors. In this study, we developed and tested a method for enhancing vein contrast using Multispectral NIR imaging and evaluated the impact of skin colour and BMI on vein visibility in a sample of 61 subjects. Our study found that the optimal wavelength for vein visibility in the NIR region was 864 nm, and the proposed method effectively enhanced vein contrast. We also found that skin colour and BMI influenced vein visibility, with fair skin and lower BMI associated with better vein visibility. Our study demonstrates the potential of NIR imaging for enhancing vein visibility, and also emphasizes in considering skin colour and BMI as significant factors. However, there were some limitations of our study, as the majority of the age group consisted of the young population and it was not inclusive of babies and elderly people for whom venous access is difficult.","PeriodicalId":191927,"journal":{"name":"2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121267158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Wearable-based Frozen Shoulder Rehabilitation Exercise Recognition using Machine Learning Approaches 基于机器学习方法的可穿戴式肩周炎康复运动识别

2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2023-06-14 DOI: 10.1109/MeMeA57477.2023.10171854

Chien-Pin Liu, Chih-Chun Lai, Kai-Chun Liu, Chia-Yeh Hsieh, Chia-Tai Chan

{"title":"Wearable-based Frozen Shoulder Rehabilitation Exercise Recognition using Machine Learning Approaches","authors":"Chien-Pin Liu, Chih-Chun Lai, Kai-Chun Liu, Chia-Yeh Hsieh, Chia-Tai Chan","doi":"10.1109/MeMeA57477.2023.10171854","DOIUrl":"https://doi.org/10.1109/MeMeA57477.2023.10171854","url":null,"abstract":"Frozen shoulder is a disease that causes shoulder pain and stiffness. It limits the range of movement of the shoulder and has a great impact on the quality of daily life. One of the common treatment methods is to do frozen shoulder rehabilitation exercises. However, patients often fail to follow the instructions of the physical therapists during the program of home-based rehabilitation. Furthermore, clinical professionals are unavailable to track and monitor the home-based rehabilitation exercise performance of patients. To support clinical monitoring, we develop a wearable-based frozen shoulder rehabilitation exercise recognizer using different machine learning models and deep learning models. The proposed methods can automatically identify movement/silence segments from continuous signals and classify types of frozen shoulder rehabilitation exercises. Besides, we propose a finite state machine and fragmentation revision mechanism for error correction. Twenty subjects are invited to perform six types of rehabilitation exercises. The proposed methods achieve the best result of 95.6% accuracy, 95.83% F-score for the identification of movement/silence and 95.58% accuracy, 95.49% F-score for classification of exercise type, respectively. The results demonstrate the feasibility of the proposed method to automatically monitor the frozen shoulder rehabilitation exercise, which has the potential to provide objective, continuous and quantitative information for telerehabilitation.","PeriodicalId":191927,"journal":{"name":"2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125398343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Murine in vivo tumor model to explain the interpretability of radiomic features. 小鼠体内肿瘤模型来解释放射学特征的可解释性。

2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2023-06-14 DOI: 10.1109/MeMeA57477.2023.10171852

A. Rifi, F. Geirnaert, Camille Raets, C. Aisati, I. Dufait, M. Ridder, K. Barbé

{"title":"Murine in vivo tumor model to explain the interpretability of radiomic features.","authors":"A. Rifi, F. Geirnaert, Camille Raets, C. Aisati, I. Dufait, M. Ridder, K. Barbé","doi":"10.1109/MeMeA57477.2023.10171852","DOIUrl":"https://doi.org/10.1109/MeMeA57477.2023.10171852","url":null,"abstract":"Medical imaging plays a crucial role in the management of oncological patients, where it is routinely used for diagnosis, staging and follow-up of tumors. Additionally, in the context of radiotherapy (RT), medical physicists utilize medical images for dose planning and accurate dose delivery. These images contain valuable information that reflects the underlying phenotype. This information can be accessed through the extraction of quantitative features that are subsequently used to design machine learning prediction models. This process is referred to as radiomics. However, the inherent non-biological-interpretability of radiomic features strongly hinders their clinical application. Therefore, we aim to unravel the biological meaning of radiomic features by performing dedicated preclinical in vivo experiments. In this study, we aimed to advance and optimize our original setup. Radiomic features from computed tomography (CT) scans of an in vivo murine tumor model were extracted. Mice were scanned, afterwards treated with RT, an oxygen-inducing drug or a combination hereof and re-scanned. Features were analyzed and compared using an exploratory factor analysis (EFA). The results revealed that some features are able to differentiate between the treatment groups. Furthermore, the features exhibited a high level of repeatability upon rescanning.","PeriodicalId":191927,"journal":{"name":"2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114946593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mapping care pathways in children with TBI using Markov Models 利用马尔可夫模型绘制TBI患儿的护理路径

2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2023-06-14 DOI: 10.1109/MeMeA57477.2023.10171883

Viktor-Jan De Deken, Koen Putman, W. Cools, K. Barbé, H. V. Deynse

{"title":"Mapping care pathways in children with TBI using Markov Models","authors":"Viktor-Jan De Deken, Koen Putman, W. Cools, K. Barbé, H. V. Deynse","doi":"10.1109/MeMeA57477.2023.10171883","DOIUrl":"https://doi.org/10.1109/MeMeA57477.2023.10171883","url":null,"abstract":"Brain injuries come with a significant societal burden. Focus should be brought not only to prevention but also towards improved quality of care. Currently, there is too much unexplainable variation in care trajectories. One category of patients less studied in this domain is pediatric traumatic brain injuries. The reason for this is lack of sufficient large numbers. To overcome this problem, administrative data holds the potential to provide a solution. By using Markov chain models, we can identify the different care pathways that patients with traumatic brain injuries take. To analyze the data, first the care pathways are clustered based on their similarity. This allowed for identification of different groups of patients who received similar care. Then, the pathways were reconstructed to form an expected care pathway for each cluster, which enabled interpretation of the care received. This study provides a novel technique for the mapping of causal care pathways for patients with traumatic brain injuries using administrative data. By identifying different care pathways, we can better understand the variation in care and work towards improving the quality of care received by patients. This is particularly important for children with traumatic brain injuries, who may have unique care needs that require specific attention.","PeriodicalId":191927,"journal":{"name":"2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126378844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automatic Platform for Upper Extremity Musculoskeletal Disorder Risks Estimation from Repetitive Actions -Preliminary results. 上肢肌肉骨骼疾病重复动作风险评估的自动平台-初步结果。

2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2023-06-14 DOI: 10.1109/MeMeA57477.2023.10171943

P. Aqueveque, Manuel Gutiérrez, Guisella Peña, Enrique I. Germany, Britam Gómez, Gustavo Retamal, P. Ortega-Bastidas

{"title":"Automatic Platform for Upper Extremity Musculoskeletal Disorder Risks Estimation from Repetitive Actions -Preliminary results.","authors":"P. Aqueveque, Manuel Gutiérrez, Guisella Peña, Enrique I. Germany, Britam Gómez, Gustavo Retamal, P. Ortega-Bastidas","doi":"10.1109/MeMeA57477.2023.10171943","DOIUrl":"https://doi.org/10.1109/MeMeA57477.2023.10171943","url":null,"abstract":"Work-related musculoskeletal disorders is a major problem for worker’s health when dealing with repetitive tasks. The Occupational Repetitive Actions Index (OCRA) is one of the most widely used methods for determining upper extremity risk from repetitive actions. Traditional risk assessment consists in observing and recording the entire workday or part of it. This observational assessment depends on the evaluator’s expertise, which lead to inter-evaluator variability in the results even for the same job. This paper presents preliminary results of a platform that combines motion capture data with a digitalized OCRA Index method to classify risks under repetitive tasks conditions. Repetitive action tasks were performed in a controlled laboratory environment on ten healthy subjects, where optical and inertial sensors were used to capture movement. Body segment positions, displacements and joint angles were fed into the platform comparing their processing time and reliability. Although results indicate that optical systems have a better performance than inertial sensors for posture evaluation, the last has better practical applicability since optical markers occlusion in the working setup induced measurement errors. In addition, inertial systems are more likely to be used on in real working scenarios due to their ease of use and portability. Finally, inertial sensors combined with the digitized OCRA index method platform effectively reduces 67% of the needed evaluation time compared to traditional observational methods.","PeriodicalId":191927,"journal":{"name":"2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128064881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Application of process mining in the management of inpatient analysis 流程挖掘在住院分析管理中的应用

2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2023-06-14 DOI: 10.1109/MeMeA57477.2023.10171882

Onorato d'Angelis, Valerio Lapadula, Manuel Iacuitto, D. Ivziku, Anna Sabatini, L. Vollero, M. Merone

{"title":"Application of process mining in the management of inpatient analysis","authors":"Onorato d'Angelis, Valerio Lapadula, Manuel Iacuitto, D. Ivziku, Anna Sabatini, L. Vollero, M. Merone","doi":"10.1109/MeMeA57477.2023.10171882","DOIUrl":"https://doi.org/10.1109/MeMeA57477.2023.10171882","url":null,"abstract":"The classification of the care pathway is able to define the clinical evolution of patients during hospitalization. It can also find the departments that are more stressed in terms of number of events or patients with complex clinical pictures. By analysing these aspects, it is possible to suggest improvements to the healthcare setting, making the health service provided more efficient. By applying the techniques of Process Mining it is possible to model the evolution of the complexity of inpatient management. In this paper, we present an application of some techniques of Process Mining starting from the data collected at Policlinico Universitario Campus Bio-Medico di Roma composed of anonymized records of patients in the period between 01/01/2016 and 31/12/2017. The patients and thus their hospitalization are described through a patient status grid, according to their level of autonomy, cognitive stability and clinical stability. This measure is used as an indirect measure of the complexity of inpatient management. The data were made compliant with the typical structure of an event log, and then the complexity of care of patients admitted to the facility was modelled, analyzing even the most stressed departments. The proposed approach suggests important information for the healthcare setting, ensuring an improvement of the services provided.","PeriodicalId":191927,"journal":{"name":"2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"528 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132504959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigating Effective Spectral Bands for Tissue Visualization in Oral Mucosa 研究口腔黏膜组织可视化的有效光谱带

2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2023-06-14 DOI: 10.1109/MeMeA57477.2023.10171937

Sneha Chand, A. Raj, S. Preejith, M. Sivaprakasam

{"title":"Investigating Effective Spectral Bands for Tissue Visualization in Oral Mucosa","authors":"Sneha Chand, A. Raj, S. Preejith, M. Sivaprakasam","doi":"10.1109/MeMeA57477.2023.10171937","DOIUrl":"https://doi.org/10.1109/MeMeA57477.2023.10171937","url":null,"abstract":"Detection of malignancies in the gastrointestinal tract through endoscopic investigations is crucial for managing the disease and improving cancer prognosis. However, current standard endoscopic procedures using white light sources have limitations in providing comprehensive tissue information. To address this issue, spectral imaging technology has been developed, which allows light to penetrate different tissue layers to capture the true spectral response of a tissue. The study discussed here focuses on using spectral imaging to image the sublingual region of the oral mucosa using a broadband light source and five different individual light illuminations to understand the characteristics of vascular structures under different wavelengths. This approach has the potential to provide valuable insights into the structure and function of different tissues and could lead to improvements in the detection and diagnosis of a wide range of diseases, including oral cancer. This study focuses on imaging the sublingual region of the oral mucosa using the broadband light source and five different individual light illuminations to understand the characteristics of vascular structures under different wavelengths. The study using Weber’s contrast, reveals that superficial blood vessels (SBV) have high contrast values at low wavelengths, while deep-seated blood vessels (DSBV) have high contrast values at higher wavelengths. This study confirms the findings of our previous study in a different system. The paper emphasizes the importance of using spectral imaging to capture comprehensive tissue information for the early detection of cancer and improved prognosis. The study highlights the need for an appropriate light source and the usage of individual LEDs for building a standalone system to effectively visualize vascular features. Further research on a larger scale is necessary to translate these findings into practical use for real-time endoscopic investigations.","PeriodicalId":191927,"journal":{"name":"2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"2151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130029866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Body measurement estimations using 3D scanner for individuals with severe motor impairments 使用3D扫描仪对严重运动障碍的个体进行身体测量估计

2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2023-06-14 DOI: 10.1109/MeMeA57477.2023.10171946

Cristina Nuzzi, Marco Ghidelli, Alessandro Luchetti, Matteo Zanetti, F. Crenna, M. Lancini

引用次数: 0