2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS)最新文献

A New Approach to Evaluation of Electroencephalograms Inter-Channel Phase Synchronization 脑电信号通道间相位同步评价的新方法

2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2018-06-01 DOI: 10.1109/CBMS.2018.00028

R. Tolmacheva, Y. Obukhov, L. Zhavoronkova

引用次数: 0

Usability Study on Mobile Processes Enabling Remote Therapeutic Interventions 实现远程治疗干预的移动过程的可用性研究

2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2018-06-01 DOI: 10.1109/CBMS.2018.00033

Marc Schickler, R. Pryss, W. Schlee, T. Probst, B. Langguth, Johannes Schobel, M. Reichert

{"title":"Usability Study on Mobile Processes Enabling Remote Therapeutic Interventions","authors":"Marc Schickler, R. Pryss, W. Schlee, T. Probst, B. Langguth, Johannes Schobel, M. Reichert","doi":"10.1109/CBMS.2018.00033","DOIUrl":"https://doi.org/10.1109/CBMS.2018.00033","url":null,"abstract":"Many studies have revealed that therapeutic homework is beneficial for the efficacy of therapies. Interestingly, the latter have been less supported by IT systems so far and, hence, therapeutic opportunities have been neglected. For example, mobile devices can be used to notify patients about assigned homework and help them to accomplish it in a timely manner. In general, the use of mobile devices as well as their sensors seem to be promising for the support of remote therapeutic interventions. In the Albatros project, we have been developing a framework that enables domain experts to flexibly define the homework required in the context of a remote therapeutic intervention. More precisely, the various tasks of a homework can be specified as a mobile process, which is then run on the mobile device of the respective patient. To realize this vision, a configurator component using a model-driven approach was developed. In particular, the Albatros configurator shall relieve domain experts from complex technical issues when defining a homework. The study presented in this paper investigates whether domain experts are actually able to use the configurator component. In particular, the study revealed three insights. First, basic interventions can be easily defined with an acceptable number of errors. Second, for defining complex interventions (e.g., using a sensor when performing an exercise) several issues could be identified that will contribute to improve the Albatros configurator. Third, additional studies are needed to evaluate the overall mental effort of domain experts when using the configurator. Altogether, the Albatros framework may be a reasonable alley to empower domain experts in creating homework in the context of remote therapeutic interventions.","PeriodicalId":229453,"journal":{"name":"2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126186985","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: 5

Improving Skin Lesion Segmentation with Generative Adversarial Networks 用生成对抗网络改进皮肤病变分割

2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2018-06-01 DOI: 10.1109/CBMS.2018.00086

Federico Bolelli, F. Pollastri, Roberto Paredes Palacios, C. Grana

引用次数: 27

RAFIKI: Retrieval-Based Application for Imaging and Knowledge Investigation RAFIKI:基于检索的影像与知识调查应用

2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2018-06-01 DOI: 10.1109/CBMS.2018.00020

Marcos Roberto Nesso Junior, M. Cazzolato, L. C. Scabora, Paulo H. Oliveira, Gabriel Spadon, J. D. Souza, Willian D. Oliveira, D. Y. T. Chino, J. F. Rodrigues, A. Traina, C. Traina

{"title":"RAFIKI: Retrieval-Based Application for Imaging and Knowledge Investigation","authors":"Marcos Roberto Nesso Junior, M. Cazzolato, L. C. Scabora, Paulo H. Oliveira, Gabriel Spadon, J. D. Souza, Willian D. Oliveira, D. Y. T. Chino, J. F. Rodrigues, A. Traina, C. Traina","doi":"10.1109/CBMS.2018.00020","DOIUrl":"https://doi.org/10.1109/CBMS.2018.00020","url":null,"abstract":"Medical exams, such as CT scans and mammograms, are obtained and stored every day in hospitals all over the world, including images, patient data, and medical reports. It is paramount to have tools and systems to improve computer-aided diagnoses based on such huge volumes of stored information. The Content-Based Image Retrieval (CBIR) is a powerful paradigm to help reaching such a goal, providing physicians with intelligent retrieval tools to present him/her with similar or complementary cases, in which visual characteristics improve textual data. Employing comparative inspection on previous cases, the physician can obtain a more comprehensive understanding of the case he/she is working on. Current hospital systems do not carry native CBIR functionalities yet, relying on add-on subsystems, which often do not adhere to the existing relational database infrastructures. In this work, we propose RAFIKI, a software prototype that extends the Relational Database Management System (RDBMS) PostgreSQL, providing native support for CBIR functionalities, modular extensibility, and seamless integration for data science tools, such as Python and R. We show the applicability of our system by evaluating three clinical scenarios, performing queries over a real-world image dataset of lung exams. Our results spot actual potential in promoting informed decision-making from the physician's perspective. Besides, the system exhibited a higher performance when compared to previous systems found in the literature. Moreover, RAFIKI contributes with a model to establish how to put together CBIR concepts and relational data, providing a powerful design for further development of theoretical and practical concepts and tools.","PeriodicalId":229453,"journal":{"name":"2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131208047","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: 5

Predicting Age of Onset in TTR-FAP Patients with Genealogical Features 有家谱特征的TTR-FAP患者的发病年龄预测

2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2018-06-01 DOI: 10.1109/CBMS.2018.00042

Maria Pedroto, A. Jorge, João Mendes-Moreira, T. Coelho

引用次数: 1

DOCToR: The Role of Deep Features in Content-Based Mammographic Image Retrieval 深度特征在基于内容的乳房x线摄影图像检索中的作用

2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2018-06-01 DOI: 10.1109/CBMS.2018.00035

R. S. Bressan, D. Alves, Lucas M. Valério, P. Bugatti, P. T. Saito

{"title":"DOCToR: The Role of Deep Features in Content-Based Mammographic Image Retrieval","authors":"R. S. Bressan, D. Alves, Lucas M. Valério, P. Bugatti, P. T. Saito","doi":"10.1109/CBMS.2018.00035","DOIUrl":"https://doi.org/10.1109/CBMS.2018.00035","url":null,"abstract":"Nowadays, deep features, obtained from a variety of deep learning architectures, play an important role in several real problems. It is know that transfer learning strategies could be employed to take advantage of such deep features trained under a general context (e.g. ImageNet). However, to the best of our knowledge, the majority of works focus on similar contexts to accomplish such transfer strategies. Thus, in this work we analyze the role of deep features in content-based medical image retrieval, and demonstrate that it is possible to make use of transfer learning from a general context to a specific medical context, like the content-based mammographic image retrieval. To do so, we evaluated several hand-crafted features against deep features acquired from state-of-the-art deep architectures through transfer learning. Extensive experiments on challenging public mammographic image datasets testify that the generalized deep features are able to improve in a great extend the precision of similarity queries both in the traditional process and applying query refinement strategies.","PeriodicalId":229453,"journal":{"name":"2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114305370","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: 11

CBMS 2018 Welcome Message and Preface CBMS 2018欢迎辞和序言

2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2018-06-01 DOI: 10.1109/cbms.2018.00005

B. Kane

引用次数: 0

Services Orchestration and Workflow Management in Distributed Medical Imaging Environments 分布式医学成像环境中的服务编排和工作流管理

2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2018-06-01 DOI: 10.1109/CBMS.2018.00037

João Rafael Almeida, T. Godinho, Luís Bastião, C. Costa, J. Oliveira

{"title":"Services Orchestration and Workflow Management in Distributed Medical Imaging Environments","authors":"João Rafael Almeida, T. Godinho, Luís Bastião, C. Costa, J. Oliveira","doi":"10.1109/CBMS.2018.00037","DOIUrl":"https://doi.org/10.1109/CBMS.2018.00037","url":null,"abstract":"Medical imaging laboratories are supported by information and communication systems commonly denominated as PACS, that encompasses technology for acquisition, archive, distribution and visualization of digital images in network. Concerning the data and workflow management, traditional solutions used in production provide a limited set of services usually configured at system installation. As result, healthcare institutions are not able to fully explore their infrastructure or adapt it to new operational requirements, either for clinical or research procedures. This article proposes a framework for services orchestration and workflow management in distributed medical imaging environments. It was designed for end-user usage and is accessible through a Web portal that allows to document, repeat and allocate procedures and tasks to correct resources, either from information systems or human interventions. It provides an abstraction layer for integration with distinct data sources through standard services, allows the creation of new services through orchestration of existent ones and the scheduling of tasks. Moreover, it includes a logging and alert mechanism integrated with email service. The solution was validated through the specification of two use cases that were deployed in production environment.","PeriodicalId":229453,"journal":{"name":"2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124629675","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: 3

Computerised Interpretation Systems for Cardiotocography for Both Home and Hospital Uses 家庭和医院用心脏造影计算机解释系统

2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2018-06-01 DOI: 10.1109/CBMS.2018.00080

Yu Lu, Yongjie Gao, Yuyang Xie, Shunan He

{"title":"Computerised Interpretation Systems for Cardiotocography for Both Home and Hospital Uses","authors":"Yu Lu, Yongjie Gao, Yuyang Xie, Shunan He","doi":"10.1109/CBMS.2018.00080","DOIUrl":"https://doi.org/10.1109/CBMS.2018.00080","url":null,"abstract":"Improving the accuracy and consistency of interpretation results for foetal monitoring has been an active research direction in both obstetrics and gynaecology. In this paper, we have developed computer-aided analysis systems for use both in hospitals and at home that incorporate automatic scoring functions to evaluate the foetal conditions in the cavity of the uterus. These systems can analyse any segment of data in a foetal monitoring record. Our novel systems can accurately identify the CTG patterns, such as FHR baseline, foetal movements, uterine contractions, accelerations and type of decelerations, thus making the interpretation results more accurate. There are two modes of scoring: automatic and manual, and the system consists of a number of popular scoring methods, including the Kreb's, Fischer, and improved Fischer scoring methods and the ACOG three-tier classification methods. According to clinical tests in hospitals, the systems have comparable accuracy to obstetricians' interpretations. Computerised interpretation thus provides a supplement to traditional analysis that could help obstetricians function more effectively.","PeriodicalId":229453,"journal":{"name":"2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124748008","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: 7

Finding Tinnitus Patients with Similar Evolution of Their Ecological Momentary Assessments 耳鸣患者生态瞬时评价演化相似的研究

2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2018-06-01 DOI: 10.1109/CBMS.2018.00027

Lakshmi Prasath Muniandi, W. Schlee, R. Pryss, M. Reichert, Johannes Schobel, Robin Kraft, M. Spiliopoulou

{"title":"Finding Tinnitus Patients with Similar Evolution of Their Ecological Momentary Assessments","authors":"Lakshmi Prasath Muniandi, W. Schlee, R. Pryss, M. Reichert, Johannes Schobel, Robin Kraft, M. Spiliopoulou","doi":"10.1109/CBMS.2018.00027","DOIUrl":"https://doi.org/10.1109/CBMS.2018.00027","url":null,"abstract":"Mobile applications can help patients with a chronical disease to record their Ecological Momentary Assessments (EMA) and to get a more precise impression of how their disease manifests itself during day and night and over longer time periods. Such crowdsensing applications contribute to patient empowerment, in which patients monitor their disease and, sometimes, learn to cope better with it. An open question is whether physicians can also be helped in assisting their patients, by understanding similarities and differences in the patients' evolution. We study the EMA of patients with the chronical disease tinnitus, as recorded with the mobile crowdsensing application Track Your Tinnitus. We propose a method that captures similarities in patient evolution, taking account of the differences in the frequency of each patient's EMA recordings. We incorporate this method into a complete workflow that encompasses following components: an algorithm that captures similarities among patients on the basis of their registration data, a method that juxtaposes static patient similarity to EMA-based patient similarity, and a method that identifies those subspaces of the static feature space and those of the EMA-based feature space, which are mainly contributing to patient similarity. We report on our results for the time period recordings from 2014 till 2017 of 450 tinnitus patients from TrackYourTinnitus mobile application.","PeriodicalId":229453,"journal":{"name":"2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129761919","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: 6