Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19最新文献_第2页

Automated Urine Microscopy Using Scale Invariant Feature Transform 基于尺度不变特征变换的自动尿液显微镜

Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19 Pub Date : 2019-03-28 DOI: 10.1145/3326172.3326186

Jennifer C. Dela Cruz, Ramon G. Garcia, Mikko Ivan D. Avilledo, John Christopher M. Buera, Rom Vincent S. Chan, Paul Gian T. Espana

引用次数: 2

Expression and Purification of Soluble Bacterially-Expressed Human Hexokinase II in E.coli System 可溶性细菌表达人己糖激酶II在大肠杆菌系统中的表达和纯化

Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19 Pub Date : 2019-03-28 DOI: 10.1145/3326172.3326219

S. Tanbin, F. A. A. Fuad

{"title":"Expression and Purification of Soluble Bacterially-Expressed Human Hexokinase II in E.coli System","authors":"S. Tanbin, F. A. A. Fuad","doi":"10.1145/3326172.3326219","DOIUrl":"https://doi.org/10.1145/3326172.3326219","url":null,"abstract":"Human hexokinase II (HKII) is one of the key enzymes in the glycolytic pathway. It has been postulated that HKII is a potential target for anti-dengue (DENV) drug development, as well as involved in cancer and tumor cell growth. In this work, the human hexokinase II (HKII) gene was cloned into pETite N-His SUMO vector and transformed into the E.coli strain HI-control 10G for the propagation of clones. Two different expression hosts, E.coli HI-controlTM BL21 (DE3) and BL21 (DE3) pLysS were used to optimize HKII expression. In order to obtain the soluble recombinant HKII in a functional form, we optimized protein expression at three different temperatures; 17°C, 25°C and 37°C, at 24 hours incubation time. The soluble protein was expressed in the presence of 0.5 mM isopropyl-2-D-thiogalactopyranoside (IPTG) in TB media at 17°C for 24 hrs. The expressed protein was then purified to homogeneity by a combination of Immobilized Metal Ion Affinity Chromatography (IMAC), size exclusion chromatography (SEC) and ion-exchange chromatography (IEX), resulting in pure bacterially-expressed HK2. Taken together, this study has successfully produced soluble bacterially-expressed human HKII that can be utilized for further therapeutic studies.","PeriodicalId":293245,"journal":{"name":"Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132890768","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: 1

Microscopic Image Analysis and Counting of Red Blood Cells and White Blood Cells in a Urine Sample 尿液样本中红细胞和白细胞的显微图像分析和计数

Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19 Pub Date : 2019-03-28 DOI: 10.1145/3326172.3326185

Jennifer C. Dela Cruz, Ramon G. Garcia, Mikko Ivan D. Avilledo, John Christopher M. Buera, Rom Vincent S. Chan, Paul Gian T. Espana

引用次数: 10

Automatic Detection of Circulating Tumor Cells with Very Deep Residual Networks 基于深度残差网络的循环肿瘤细胞自动检测

Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19 Pub Date : 2019-03-28 DOI: 10.1145/3326172.3326224

Bin Li, Yunhao Ge, Yanzheng Zhao, W. Yan

{"title":"Automatic Detection of Circulating Tumor Cells with Very Deep Residual Networks","authors":"Bin Li, Yunhao Ge, Yanzheng Zhao, W. Yan","doi":"10.1145/3326172.3326224","DOIUrl":"https://doi.org/10.1145/3326172.3326224","url":null,"abstract":"Automatic detection of circulating tumor cells (CTCs) in microscopic images is a very challenging task due to the variable artificial and environmental factors, such as inconsistency of light intensity and staining, cell adhesion, multiple impurities and so on. In order to meet these challenges, we propose a novel deep multiscale residual network (DMRN) for CTCs detection. Compared with existing methods either low-level hand-crafted features or CNNs with shallower architectures, our deep networks can acquire more discriminative features for more accurate detection. To train very deep networks more efficiently, we propose a set of schemes to ensure effective training and learning under limited training data. First, we apply the residual learning to generate more discriminative features and overcome the overfitting problem when a network goes to deeper. Then, a fully residual convolutional network (FRCN) is proposed to produce the prediction maps of CTCs. Finally, we propose to integrate multi-scale contextual information in proposed FRCN and fuse these prediction maps both global and local features of CTCs, making the prediction more accurate and robust. We built three DMRN models to study the impact of network depth on model performance. Each model was tested on our own dataset containing complex jamming information. The DRMN-50 model which has a depth of 50 layers performs best among three models with Jaccard-index of 0.810 (with a pixel accuracy of 99.8% as a reference index) and its performance outperform other existing state-of-art methods such as U-Net in other domain. The result also depicts the accurate and robust performance of proposed method in complex environment.","PeriodicalId":293245,"journal":{"name":"Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123990527","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: 1

Rapid Microscopic Analysis Using Natural Neighbor Interpolation 基于自然邻域插值的快速显微分析

Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19 Pub Date : 2019-03-28 DOI: 10.1145/3326172.3326218

G. Sampedro, M. Soriano, A. Yumang, Ericson D. Dimaunahan

引用次数: 5

Experimental Study on Bone Health in Drilling 钻孔中骨骼健康的实验研究

Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19 Pub Date : 2019-03-28 DOI: 10.1145/3326172.3326181

K. Alam, A. Al-Ghaithi, Mushtaq Khan

引用次数: 0

A Novel Assessment Technique for the Degree of Facial Symmetry Before and After Orthognathic Surgery Based on Three-Dimensional Contour Features Using Deep Learning Algorithms 一种基于三维轮廓特征的深度学习正颌手术前后面部对称度评估方法

Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19 Pub Date : 2019-03-28 DOI: 10.1145/3326172.3326222

Hsiu-Hsia Lin, L. Lo, Wen-Chung Chiang

{"title":"A Novel Assessment Technique for the Degree of Facial Symmetry Before and After Orthognathic Surgery Based on Three-Dimensional Contour Features Using Deep Learning Algorithms","authors":"Hsiu-Hsia Lin, L. Lo, Wen-Chung Chiang","doi":"10.1145/3326172.3326222","DOIUrl":"https://doi.org/10.1145/3326172.3326222","url":null,"abstract":"Improvement of the facial asymmetry has become as important as correction of the malocclusion in the evaluation and planning for orthognathic surgery. In this study, we proposed an automatic machine learning system (DLS) to extract three-dimensional (3D) contour features and assess the degree of facial symmetry in patients treated with orthognathic surgery. A total of 500 normal populations were included to construct the DLS. The ground truth was based on an average of the survey of 50 of diverse referees offering their facial symmetry ratings over a 10-point scale for 500 3D facial images via an auto-play and separate slide show. The facial region of interest (ROI) was extracted by removing the disturbed region, such as the ears, the neck and all points above the hairline. A contour map was extracted from the ROI image, and used as an input pattern for automatic DLS, which included a deep convolutional neural network (CNN) for feature extraction, and a regression network provided for prediction. The experimental results showed that our model achieved 78.85% accuracies on held-out test patterns. The facial symmetry degree assessment within 1 degree was 98.63%. In addition, our method was compared with conventional 2D approaches, which obtained better results than 2D-only features which resulted accuracy is 65% using the same sample size, and the CNN system. For clinical application, 100 patients with facial asymmetry were enrolled in evaluating facial symmetry improvement after orthognathic surgery. A paired t-test was used to compare the significance of the differences between the pre-surgery and post- surgery assessing result of facial symmetry using DLS, with p <0.05 considered significant. The mean of preoperative facial symmetry degree (0.92 ± 0.17) was higher than of postoperative (0.65 ± 0.13) with a significant improvement (p = 0.021).","PeriodicalId":293245,"journal":{"name":"Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131899292","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: 2

Attempt to Visualize Cardiac Motion on Body Surface Using Active Stereoscopic Depth Camera 尝试使用主动立体深度摄像机在体表上可视化心脏运动

Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19 Pub Date : 2019-03-28 DOI: 10.1145/3326172.3326226

H. Aoki, T. Shiga, A. Suzuki, Koichi Takeuchi

引用次数: 0

Application of Reflectance Mode Photoplethysmography for Non-Invasive Monitoring of Blood Glucose Level with Moving Average Filter 反射模式光容积脉搏波在移动平均滤波器无创监测血糖水平中的应用

Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19 Pub Date : 2019-03-28 DOI: 10.1145/3326172.3326190

F. Cruz, C. Paglinawan, Celina Nadine V. Catindig, John Charles B. Lamchek, Danielle Diane C. Almiranez, Anne Flereece Sanchez

{"title":"Application of Reflectance Mode Photoplethysmography for Non-Invasive Monitoring of Blood Glucose Level with Moving Average Filter","authors":"F. Cruz, C. Paglinawan, Celina Nadine V. Catindig, John Charles B. Lamchek, Danielle Diane C. Almiranez, Anne Flereece Sanchez","doi":"10.1145/3326172.3326190","DOIUrl":"https://doi.org/10.1145/3326172.3326190","url":null,"abstract":"With the continuous increase in number of people suffering from diabetes, the demand of a device that can noninvasively monitor blood glucose level has been greater. The goal of the study is to develop a device that can monitor the blood glucose level that would not cause any discomfort to the patients by utilizing reflectance mode photoplethysmography equipped with a filtering technique, Moving Average filter. Initially, the device prompts the user to choose from two categories depending on his condition: diabetic or non-diabetic, and then would choose between the two modes: fasting or post meal mode. The parameters utilized in the study are the force in Newton (N) which corresponds to the applied pressure on the finger, the peak-to-peak voltage (V) of the photopletyhsmography signal, and lastly, the blood glucose level measured in milligram per deciliter (mg/dL). The force is acquired using a force sensitive resistor that is incorporated in the ring. The suggested device employs a photoplethysmography sensor which can diagnose variations on microvascular bed of tissue. The variations in the distribution of blood volume have a significant relation with the measurement of blood glucose level. The technique used to estimate the photoplethysmography in terms of peak-to-peak voltage is the Moving Average filter, and the result is then compared to that of the OneTouch glucometer and Fasting Plasma Glucose. From the results acquired, two equations are derived which output the blood glucose level for diabetic and non-diabetic patients in mg/dL. The equations are described to be both linear, a positive correlation for non-diabetic patients with a percentage of 70.3004% and a negative correlation for the diabetic with a percentage of 91.9226%.","PeriodicalId":293245,"journal":{"name":"Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134406457","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: 4

Fundus Image Classification for Diabetic Retinopathy Using Disease Severity Grading 基于疾病严重程度分级的糖尿病视网膜病变眼底图像分类

Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19 Pub Date : 2019-03-28 DOI: 10.1145/3326172.3326198

A. Sakaguchi, R. Wu, S. Kamata

{"title":"Fundus Image Classification for Diabetic Retinopathy Using Disease Severity Grading","authors":"A. Sakaguchi, R. Wu, S. Kamata","doi":"10.1145/3326172.3326198","DOIUrl":"https://doi.org/10.1145/3326172.3326198","url":null,"abstract":"Diabetic Retinopathy (DR) is ranked at the top of blindness causes. It progresses without subjective symptoms and leads to blindness in the worst case. However early detections and proper treatments can prevent visual disturbance. Because it takes time and cost for diagnoses by clinicians, research and development of diagnostic support systems has actively been conducted. This research aims to establish a fundus image classification method based on disease severity assessment for a diagnostic support by a fundus image analysis. In this paper, we propose a Graph Neural Network (GNN)-based method to improve accuracy for severity classification. Our method has two features. The first is to extract Region-Of-Interest (ROI) sub-images focusing on regions locally capturing lesions in order to minimize background noise in image preprocessing for the classification. The second is to utilize the GNN which is not yet applied for fundus image classification. In order to evaluate our proposed method, we use Indian Diabetic Retinopathy Image Dataset (IDRiD) utilized in \"Diabetic Retinopathy: Segmentation and Grading Challenge\" on Biomedical Imaging held at the IEEE International Symposium in 2018. We verified that the accuracy of our method improved 2.9% over the conventional method in this contest.","PeriodicalId":293245,"journal":{"name":"Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology - ICBET' 19","volume":"5 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114026855","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: 18