Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing最新文献_第2页

Automatic Classification of Plasmodium for Malaria Diagnosis based on Ensemble Neural Network 基于集成神经网络的疟疾诊断中疟原虫自动分类

Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing Pub Date : 2020-04-23 DOI: 10.1145/3399637.3399641

Lulin Shi, Zhen Guan, Chunzi Liang, Haihang You

{"title":"Automatic Classification of Plasmodium for Malaria Diagnosis based on Ensemble Neural Network","authors":"Lulin Shi, Zhen Guan, Chunzi Liang, Haihang You","doi":"10.1145/3399637.3399641","DOIUrl":"https://doi.org/10.1145/3399637.3399641","url":null,"abstract":"Malaria is one of the important public health issues of global concern. It is a kind of infectious disease caused by Plasmodium which can endanger human life and health. The examination of Plasmodium blood smear is the main method to diagnose malaria. Applying machine learning method to automatically analyze malaria smear images is very important for rapid diagnosis and surveillance of malaria. However, the existing machine learning methods need further improvement in feature extraction and generalization ability. For this reason, this paper introduces an ensemble neural network to automatically learn more accurate image features and achieve automatic classification of malaria images. In addition, we propose an adaptive threshold control method for cell segmentation, and then put the cell as center to extract images to obtain the training dataset, which solves the noise problem caused by sliding window cutting. And the idea of transfer learning is applied to solve the problem of shortage of training data. We additionally apply the proposed method to malaria image recognition and achieve 94.58% accuracy. The experimental results show that the model has good robustness and generalization ability and provides a valid data processing method for clinical malaria rapid diagnosis application.","PeriodicalId":248664,"journal":{"name":"Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115505870","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

Unique Indexing of Penrose Tiles and Its Application to Information-Bearing Markers 彭罗斯瓷砖的独特标引及其在信息标记中的应用

Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing Pub Date : 2020-04-23 DOI: 10.1145/3399637.3399655

Hiroshi Ito

引用次数: 0

Dynamic Monitoring of Intestinal Ischemia-reperfusion Injury in Rats by Photoacoustic Tomography 光声断层成像对大鼠肠缺血再灌注损伤的动态监测

Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing Pub Date : 2020-04-23 DOI: 10.1145/3399637.3399647

Ten Pan, Jinge Yang, Huabei Jiang

引用次数: 0

A Framework of Student's-t Mixture Model for Accurate and Robust Point Set Registration 一种精确鲁棒的Student -t混合模型配准框架

Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing Pub Date : 2020-04-23 DOI: 10.1145/3399637.3399639

Zhiyong Zhou, Guangqiang Chen, G. Fan, Jiansong Ji, Yakang Dai

{"title":"A Framework of Student's-t Mixture Model for Accurate and Robust Point Set Registration","authors":"Zhiyong Zhou, Guangqiang Chen, G. Fan, Jiansong Ji, Yakang Dai","doi":"10.1145/3399637.3399639","DOIUrl":"https://doi.org/10.1145/3399637.3399639","url":null,"abstract":"An accurate and robust point set registration framework using Student's-t mixture model is proposed in this paper due to the Gaussian mixture model being vulnerable by the outliers, noise and the data with longer than normal tails. The key idea of this point set registration framework is to theoretically consider Student's-t mixture model as a generalization of the well know Gaussian mixture model. In the proposed framework, we firstly model the correspondences of two point sets by using Student's-t mixture model, where one point set is considered as data observations and the other one as components of Student's-t mixture model respectively. Secondly, we separate parameters of registration parameters and transformation from the mixture model by using negative log-likelihood function for getting a simple optimization. Thirdly, we get general solutions of registration parameters and transformation in cases of rigid, affine, and non-rigid by EM method. Finally, we show the similarity of deformation parameters between Gaussian mixture model and the proposed framework based on Student's-t mixture models, and theoretically analyze the reason of similarity from the view of the Bayes method. We compare our framework with other state-of-the-art point set registration methods based on finite mixture models on both various 2D and 3D point sets identified from clinical medical images on rigid, affine, and non-rigid cases, where the proposed framework demonstrates its statistical accuracy and robustness, outperforming other competing methods.","PeriodicalId":248664,"journal":{"name":"Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116395959","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

Tomographic Image Deblurring Using Steepest Descent 使用最陡下降层析图像去模糊

Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing Pub Date : 2020-04-23 DOI: 10.1145/3399637.3399640

N. R. Jaffri, L. Shi, Usama Abrar

引用次数: 0

In vivo Monitoring Hemodynamic Changes in Finger Vessels Using Photoacoustic Tomography 利用光声断层成像在体内监测手指血管的血流动力学变化

Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing Pub Date : 2020-04-23 DOI: 10.1145/3399637.3399646

Man Wu, Qiquan Shang, Jinge Yang, Lin Huang, Huabei Jiang

引用次数: 1

Detection of Artificial Tooth Cracks based on Optical Coherence Tomography 基于光学相干层析成像的人工牙裂纹检测

Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing Pub Date : 2020-04-23 DOI: 10.1145/3399637.3399654

Shi Boya, Tang Yan, L. Xiaoli, Bai Xijing, Meng Zhuo

引用次数: 0

Research on Performance of Indoor LoRaWAN Network based on NS3 基于NS3的室内LoRaWAN网络性能研究

Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing Pub Date : 2020-04-23 DOI: 10.1145/3399637.3399644

Xiao Ma, Weimin Hou, Jia Su, Haining Li

引用次数: 0

Compound Kushen Injection combined with Chemotherapy in Advanced Gastric Cancer: A Systematic Review and Meta-Analysis 复方苦参注射液联合化疗治疗晚期胃癌:系统评价和meta分析

Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing Pub Date : 2020-04-23 DOI: 10.1145/3399637.3399653

Yi-Fan Su, De-hui Li, Huan-fang Fan, Chun-xia Sun

{"title":"Compound Kushen Injection combined with Chemotherapy in Advanced Gastric Cancer: A Systematic Review and Meta-Analysis","authors":"Yi-Fan Su, De-hui Li, Huan-fang Fan, Chun-xia Sun","doi":"10.1145/3399637.3399653","DOIUrl":"https://doi.org/10.1145/3399637.3399653","url":null,"abstract":"Objective: To evaluate the clinical efficacy and safety of compound Kushen injection combined with chemotherapy in the treatment of advanced gastric cancer. Methods: A computerized search through PubMed, MEDLINE, CNKI, Web of Science and Baidu Scholar electronic databases was performed to obtain randomized controlled trials (RCTs) that compared the efficacy and safety of compound Kushen injection plus chemotherapy in patients with advanced gastric cancer with chemotherapy alone, covering all papers published up to 20 January 2020. The quality of the included literature was evaluated using the Cochrane-rereviewer's Handbook 5.1 evaluation criteria, and the data was analyzed by Rev-Man5.3 analysis software. Results: a total of 1744 patients with advanced gastric cancer were enrolled in 21 RCT studies. Meta analysis results show that: Compared with chemotherapy alone, compound Kushen injection combined with chemotherapy improved the total effective rate (OR=1.89; 95% CI:1.56-2.31, P<0.00001), pain relief rate (OR=3.15; 95% CI: 1.81-5.50, P<0.0001), and thrombocytopenia rate (OR=0.51; 95% CI:0.31-0.85, P=0.009) in the treatment of advanced gastric cancer. Conclusion: Compound Kushen injection combined with chemotherapy in the treatment of advanced gastric cancer can effectively improve the clinical efficacy, relieve pain, reduce chemotherapy-induced thrombocytopenia and other adverse reactions, which is worthy of clinical application.","PeriodicalId":248664,"journal":{"name":"Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124401983","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

Comparison and Evaluation of Video Retrieval Approaches Using Query Sentences 基于查询句的视频检索方法的比较与评价

Proceedings of the 2020 2nd International Conference on Intelligent Medicine and Image Processing Pub Date : 2020-04-23 DOI: 10.1145/3399637.3399657

K. Ueki, Takayuki Hori

引用次数: 0