Tianming Zhan, Yongzhao Zhan, Yao Ji, Shenghua Gu, Jin Wang, Lei Jiang
{"title":"Brain Tumor Segmentation in Multi-modality MRIs Using Multiple Classifier System and Spatial Constraint","authors":"Tianming Zhan, Yongzhao Zhan, Yao Ji, Shenghua Gu, Jin Wang, Lei Jiang","doi":"10.1109/CIA.2015.12","DOIUrl":"https://doi.org/10.1109/CIA.2015.12","url":null,"abstract":"Delineating brain tumor boundaries from multi-modality magnetic resonance images (MRIs) is a crucial step in brain cancer surgical and treatment planning. In this paper, we propose a fully automatic technique for brain tumor segmentation from multi-modality human brain MRIs. We first use the intensities of different modalities in MRIs to represent the features of both normal and abnormal tissues. Then, the multiple classifier system (MCS) is applied to calculate the probabilities of brain tumor and normal brain tissue in the whole image. At last, the spatial-contextual information is proposed by constraining the classified neighbors to improve the classification accuracy. Our method was evaluated on 20 multi-modality patient datasets with competitive segmentation results.","PeriodicalId":176961,"journal":{"name":"2015 3rd International Conference on Computer, Information and Application","volume":"46 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130795555","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}
Yang Yang, Jinfu Chen, Yongzhao Zhan, Xinyu Wang, Jin Wang, Zhanzhan Liu
{"title":"Low Level Segmentation of Motion Capture Data Based on Cosine Distance","authors":"Yang Yang, Jinfu Chen, Yongzhao Zhan, Xinyu Wang, Jin Wang, Zhanzhan Liu","doi":"10.1109/CIA.2015.14","DOIUrl":"https://doi.org/10.1109/CIA.2015.14","url":null,"abstract":"3D motion capture is to track and record human movements. In recent years, it has been applied into many fields, such as human computer interaction, animation, etc. Low-level segmentation of motion capture data is of significance to the various applications of 3D motion capture, however, due to the high dimensionality of motion capture data, traditional low-level segmentation methods can hardly work out a suitable segmentation for motion capture data. In order to solve this problem, a low-level temporal segmentation algorithm based on cosine distance is proposed, hierarchical clustering is explored so that similar velocity vectors are clustered together according to the cosine distance in a progressive way, the center of each cluster is updated as the vector derived with linear regression, the segment boundaries are determined as the point when the cosine distance between adjacent velocity vectors is greater than 1 (angle>90 degrees). We have conducted experiments on the motion capture database provided by Carnegie Mellon University (CMU), the experiment results show that the performance of the proposed method is optimistic.","PeriodicalId":176961,"journal":{"name":"2015 3rd International Conference on Computer, Information and Application","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129879825","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}
Heba Ayeldeen, Mohamed Abd Elfattah, O. Shaker, A. Hassanien, Tai-hoon Kim
{"title":"Case-Based Retrieval Approach of Clinical Breast Cancer Patients","authors":"Heba Ayeldeen, Mohamed Abd Elfattah, O. Shaker, A. Hassanien, Tai-hoon Kim","doi":"10.1109/CIA.2015.17","DOIUrl":"https://doi.org/10.1109/CIA.2015.17","url":null,"abstract":"Breast cancer is a syndrome that needs to be evaluated and well treated on the early stages to avoid any metastasis stage upgrading. Not just medical treatment is acquired, but also the usage of artificial intelligence and software technologies aid in the early detection of breast cancer. After using Case based Reasoning as a knowledge management as well as artificial intelligence system with Random Forest classifier, result yields to overall accuracy of 99%.","PeriodicalId":176961,"journal":{"name":"2015 3rd International Conference on Computer, Information and Application","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127127843","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}
{"title":"Banalization of Achromatic and Chromatic Images","authors":"Gwanggil Jeon, M. Anisetti, Wei Wu","doi":"10.1109/CIA.2015.15","DOIUrl":"https://doi.org/10.1109/CIA.2015.15","url":null,"abstract":"This paper presents a dithering technique where random weight assignment process is used. We used 3-by-3 window for dithering technique where four coefficient values were randomly assigned, right, left-down, down, and right-down locations are determined accordingly. The sum of all weights is one to maintain the original intensity of an image. Experiments were conducted on an artificial image. Results show that the proposed technique provides satisfactory quality.","PeriodicalId":176961,"journal":{"name":"2015 3rd International Conference on Computer, Information and Application","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115245065","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}
Jianjun Li, Minshe Zhang, Dong Li, Wei Zhang, Jin Wang
{"title":"Study on Open Access Construction in NSFC","authors":"Jianjun Li, Minshe Zhang, Dong Li, Wei Zhang, Jin Wang","doi":"10.1109/CIA.2015.11","DOIUrl":"https://doi.org/10.1109/CIA.2015.11","url":null,"abstract":"Open Access (OA) is developing very fast in recent years. It can help to stimulate free scientific achievements propagation via Internet and promotes academic exchange and fast publishing in an efficient and cheap way. Here, we proposed a construction scheme of our NSFC open access library which is under development. We propose the overall architecture for OA library. Then, we present detailed design from upper layer OA webpage to the mid layer some key function modules. Finally, the bottom layer raw data acquisition modules are explained with illustrative figures and table.","PeriodicalId":176961,"journal":{"name":"2015 3rd International Conference on Computer, Information and Application","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133228236","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}
Shenghua Gu, Yao Ji, Yunjie Chen, Jin Wang, Jeong-Uk Kim
{"title":"Study on Breast Mass Segmentation in Mammograms","authors":"Shenghua Gu, Yao Ji, Yunjie Chen, Jin Wang, Jeong-Uk Kim","doi":"10.1109/CIA.2015.13","DOIUrl":"https://doi.org/10.1109/CIA.2015.13","url":null,"abstract":"Breast cancer is regarded as one of the most frequent mortality causes among women. It is very important to create a system to diagnose suspicious masses in mammograms for early breast cancer detection. In this paper, we propose an automatic breast mass segmentation method based on patch merging method and generalized hierarchical Fuzzy C Means (GHFCM). The patch merging method is used to obtain the adaptive region of interest (ROI), while the GHFCM method which is able to overcome the drawbacks of effect of image noise and Euclidean distance FCM which is sensitive to outliers is used to obtain the precisely mass segmentation results. The new method is evaluated over Mini MIAS dataset. The segmentation performance from experimentations demonstrates that our method outperforms the other compared methods.","PeriodicalId":176961,"journal":{"name":"2015 3rd International Conference on Computer, Information and Application","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114703010","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}
{"title":"Three Dimensional Cloud Modeling Approach Based on L-System","authors":"SeokYoon Kang, Ki-Il Kim","doi":"10.1109/CIA.2015.9","DOIUrl":"https://doi.org/10.1109/CIA.2015.9","url":null,"abstract":"Typical methods for cloud modeling in simulation software are usually classified into static and dynamic modeling. While static modeling is accomplished by modeling tool such as 3ds max, dynamic modeling is implemented by particle system. In the former one, it is very hard to create a variety of realistic cloud models due to long implementation time. On the other hand, in the dynamic modeling case, rendering speed becomes slow because of computing overhead to handle large number of particles. Based on mentioned features of two schemes, it is required to create realistic three dimensional cloud model with small computing overhead. In order to fulfill this requirement, in this paper, we propose a cloud modeling and rendering approach based on L-system which is expected to provide scalability and low complexity. To create cloud, existing cloud dynamic model is transformed to rules of L-system in recursive way. In order to verify applicability of the proposed method, we present experimental result which is implemented by Open Scene Graph (OSG) library.","PeriodicalId":176961,"journal":{"name":"2015 3rd International Conference on Computer, Information and Application","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116907589","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}
{"title":"Towards a Computational Human Behavioral Model","authors":"M. Kilany, A. Adl, A. Hassanien, Tai-hoon Kim","doi":"10.1109/CIA.2015.18","DOIUrl":"https://doi.org/10.1109/CIA.2015.18","url":null,"abstract":"This paper introduces a computational model capable of receiving human behavior patterns, extracting relations and generating new inferences and insights about targeted actors as well as predictions about expected patterns of behavior. Designing an abstract behavior model is the core problem being solved here to reach behavioral analysis goals such as relations extraction, insights generation and prediction. The level of abstraction is being achieved by defining abstract data structures that can receive, qualify and quantify behavioral information for a targeted person, as well as the definition of logical and mathematical relations among data structures using a set of logical and mathematical rules. Identifying data and logic elements properly leads to a behavioral model that can be the basis of any intelligent computer system understanding human behavior and responding according to human needs. Revolution in human-machine interfaces and sensory technology made any computer system capable of capturing natural human input. However, systems are still limited in how such input is interpreted.","PeriodicalId":176961,"journal":{"name":"2015 3rd International Conference on Computer, Information and Application","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122647357","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}
{"title":"A Framework for Optimizing Resource Allocation in Clouds","authors":"Yeongho Choi, Yujin Lim","doi":"10.1109/CIA.2015.10","DOIUrl":"https://doi.org/10.1109/CIA.2015.10","url":null,"abstract":"Cloud computing is one of the latest computing techniques. Cloud providers provision computing resources into virtual machines and allocate them to cloud users. The cloud computing has purpose to maximize the performance such as provider revenue and customer utility. In this paper, to maximize the profit and resource utilization of the provider, we propose winner determination mechanism with considering of the penalty cost due to SLA violation in a combinatorial auction. To evaluate the effectiveness of our mechanism, we show the performance evaluation with real workload data.","PeriodicalId":176961,"journal":{"name":"2015 3rd International Conference on Computer, Information and Application","volume":"300 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131802112","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}
{"title":"Design of Conformance Testing Framework for IP-Based Wireless Sensor Networks","authors":"Young-Joo Kim, Sungmin Hong, Ok-Kyoon Ha","doi":"10.1109/CIA.2015.8","DOIUrl":"https://doi.org/10.1109/CIA.2015.8","url":null,"abstract":"Wireless sensor networks have gained immense popularity for decades and a new approach, IP-based WSNs, has recently emerged as a future technology advancing the era of ubiquitous computing. Thus, this paper designs a conformance testing framework suitable for IP-WSNs. The framework is an automatic testing methodology that consists of a test agent as a test executor located on the Internet side, a test manager in a gateway that manages testing jobs and test cases, and a software under test (SUT), which represents the actual target in the sensor nodes. The testing framework leverages the useful method of existing tools, complements their drawback.","PeriodicalId":176961,"journal":{"name":"2015 3rd International Conference on Computer, Information and Application","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132889942","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}