Pub Date : 2013-06-20DOI: 10.1109/CBMS.2013.6627765
A. Budai, A. Aichert, Bronislav Vymazal, J. Hornegger, G. Michelson
Fundus imaging is one of the most frequently used modalities for screening, diagnosis of eye diseases and some vascular abnormalities. Due to its wide availability, automatic evaluation of fundus images offers great potential benefits to current clinical practice. The basis of many automatic evaluations or diagnosis is the segmentation of the eye background, most notably, the detection of the optic disk and the segmentation of the retinal vessel tree. In this work we propose a variant of the fast radial symmetry transform (FRST), adapted to its application in the detection of the optic disk in fundus images. We evaluated and compared the performance of our method to the standard FRST and the similar, gradient based circular Hough transform using 45 images of a high resolution database with gold standard information available. We demonstrated in our experiments that the proposed method outperforms the state-of-the-art algorithms with 0.051 ± 0.073 optic disk diameter localization error in average.
{"title":"Optic disk localization using fast radial symmetry transform","authors":"A. Budai, A. Aichert, Bronislav Vymazal, J. Hornegger, G. Michelson","doi":"10.1109/CBMS.2013.6627765","DOIUrl":"https://doi.org/10.1109/CBMS.2013.6627765","url":null,"abstract":"Fundus imaging is one of the most frequently used modalities for screening, diagnosis of eye diseases and some vascular abnormalities. Due to its wide availability, automatic evaluation of fundus images offers great potential benefits to current clinical practice. The basis of many automatic evaluations or diagnosis is the segmentation of the eye background, most notably, the detection of the optic disk and the segmentation of the retinal vessel tree. In this work we propose a variant of the fast radial symmetry transform (FRST), adapted to its application in the detection of the optic disk in fundus images. We evaluated and compared the performance of our method to the standard FRST and the similar, gradient based circular Hough transform using 45 images of a high resolution database with gold standard information available. We demonstrated in our experiments that the proposed method outperforms the state-of-the-art algorithms with 0.051 ± 0.073 optic disk diameter localization error in average.","PeriodicalId":20519,"journal":{"name":"Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83820622","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}
Pub Date : 2013-06-20DOI: 10.1109/CBMS.2013.6627772
Rafael L. Dias, Renato Bueno, M. X. Ribeiro
Content-Based Image Retrieval (CBIR) Systems allow the search of images by similarity employing a numeric representation automatically or semi-automatically obtained from them to perform the search. Nevertheless, the query result does not always bring what the user expected. In this sense, CBIR systems face the semantic gap problem. One way of overcoming this problem is by the addition of diversity in query execution, so that the user can ask the system to return the most varied images regarding some similarity criteria. However, applying diversity on large datasets has a prohibitive computational cost and, moreover, the result often differs from the expected with a resulting subset that has images with high dissimilarity to the query image. In this paper we propose an approach to reduce the computational cost of Content-Based Image Retrieval systems regarding similarity and diversity criteria. The proposed approach employs dataset fractals analysis to estimate a suitable radius for a database subset to perform a similarity query regarding diversity. It selects closer images to the query center and applies the diversity factor to the subset, providing not only a better comprehension of the impact of the diversity factor to the query result, but also an improvement in execution time.
{"title":"Reducing the complexity of k-nearest diverse neighbor queries in medical image datasets through fractal analysis","authors":"Rafael L. Dias, Renato Bueno, M. X. Ribeiro","doi":"10.1109/CBMS.2013.6627772","DOIUrl":"https://doi.org/10.1109/CBMS.2013.6627772","url":null,"abstract":"Content-Based Image Retrieval (CBIR) Systems allow the search of images by similarity employing a numeric representation automatically or semi-automatically obtained from them to perform the search. Nevertheless, the query result does not always bring what the user expected. In this sense, CBIR systems face the semantic gap problem. One way of overcoming this problem is by the addition of diversity in query execution, so that the user can ask the system to return the most varied images regarding some similarity criteria. However, applying diversity on large datasets has a prohibitive computational cost and, moreover, the result often differs from the expected with a resulting subset that has images with high dissimilarity to the query image. In this paper we propose an approach to reduce the computational cost of Content-Based Image Retrieval systems regarding similarity and diversity criteria. The proposed approach employs dataset fractals analysis to estimate a suitable radius for a database subset to perform a similarity query regarding diversity. It selects closer images to the query center and applies the diversity factor to the subset, providing not only a better comprehension of the impact of the diversity factor to the query result, but also an improvement in execution time.","PeriodicalId":20519,"journal":{"name":"Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85950303","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}
Pub Date : 2013-06-20DOI: 10.1109/CBMS.2013.6627817
Dario Cavada, Manfred Mitterer, F. Ricci, O. Moling, F. Zini
Ospedale Amico (Friendly Hospital) is a mobile and personalized information system, aimed at improving the quality of the communication between medical staff and patients. The system provides the patients with up-to-date and context dependent day hospital activity guidance, and let them enter personal data and browse user-adapted descriptions of their disease. In this paper we describe the system functionality an discuss how we have addressed the limitations identified in the field study of an earlier prototype.
{"title":"A multi-functional mobile information system for hospital assistance","authors":"Dario Cavada, Manfred Mitterer, F. Ricci, O. Moling, F. Zini","doi":"10.1109/CBMS.2013.6627817","DOIUrl":"https://doi.org/10.1109/CBMS.2013.6627817","url":null,"abstract":"Ospedale Amico (Friendly Hospital) is a mobile and personalized information system, aimed at improving the quality of the communication between medical staff and patients. The system provides the patients with up-to-date and context dependent day hospital activity guidance, and let them enter personal data and browse user-adapted descriptions of their disease. In this paper we describe the system functionality an discuss how we have addressed the limitations identified in the field study of an earlier prototype.","PeriodicalId":20519,"journal":{"name":"Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84017693","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}
Pub Date : 2013-06-20DOI: 10.1109/CBMS.2013.6627801
Alexis Eid, V. Charisis, L. Hadjileontiadis, G. Sergiadis
Wireless Capsule Endoscopy (WCE) is a fairly new technology that offers a low-risk, non invasive visual inspection of the patient's digestive tract, especially the small bowel, that was previously unreachable using the traditional endoscopic methods. However, the large amount of images produced by WCE requires a highly trained physician to manually inspect them; a procedure that is time consuming and prone to human error. This was the rationale to propose a novel strategy for automatic detection of WCE images related to ulcer, one of the most common findings of the digestive tract. This paper introduces a new texture extraction method based on the Discrete Curvelet Transform (DCT), a recent multi-resolution analysis tool. Textural information is acquired by calculating the lacunarity index of DCT subbands of the WCE images. The classification step is performed by a Support Vector Machine (SVM), demonstrating promising classification accuracy (86.5%) and pointing towards further research in this field.
{"title":"A curvelet-based lacunarity approach for ulcer detection from Wireless Capsule Endoscopy images","authors":"Alexis Eid, V. Charisis, L. Hadjileontiadis, G. Sergiadis","doi":"10.1109/CBMS.2013.6627801","DOIUrl":"https://doi.org/10.1109/CBMS.2013.6627801","url":null,"abstract":"Wireless Capsule Endoscopy (WCE) is a fairly new technology that offers a low-risk, non invasive visual inspection of the patient's digestive tract, especially the small bowel, that was previously unreachable using the traditional endoscopic methods. However, the large amount of images produced by WCE requires a highly trained physician to manually inspect them; a procedure that is time consuming and prone to human error. This was the rationale to propose a novel strategy for automatic detection of WCE images related to ulcer, one of the most common findings of the digestive tract. This paper introduces a new texture extraction method based on the Discrete Curvelet Transform (DCT), a recent multi-resolution analysis tool. Textural information is acquired by calculating the lacunarity index of DCT subbands of the WCE images. The classification step is performed by a Support Vector Machine (SVM), demonstrating promising classification accuracy (86.5%) and pointing towards further research in this field.","PeriodicalId":20519,"journal":{"name":"Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78982533","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}
Pub Date : 2013-06-20DOI: 10.1109/CBMS.2013.6627756
Paulo E. S. Barbosa, M. Morais, K. Galdino, Melquisedec Andrade, L. Gomes, F. Moutinho, J. Figueiredo
Medical devices development and validation are difficult activities due to the critical nature of these products, involving risks to the human lives. Moreover, regulatory agencies are increasing the control over companies because of the still huge number of harms caused for several reasons, having software failures as one of the main causes. Thus it is clear that more formal and sophisticated software development techniques should be investigated. In this paper, we show how Petri nets can play the role of a generic framework for architectural decisions for control systems, allowing besides verification/simulation, an important bridge in the requested traceability by regulatory bodies. We claim that it is possible to satisfy traceability from architectural elements to code, test cases, functional and safety requirements and so on. In order to make clear our point, we conducted a case study from a generic infusion pump specification.
{"title":"Towards medical device behavioural validation using Petri nets","authors":"Paulo E. S. Barbosa, M. Morais, K. Galdino, Melquisedec Andrade, L. Gomes, F. Moutinho, J. Figueiredo","doi":"10.1109/CBMS.2013.6627756","DOIUrl":"https://doi.org/10.1109/CBMS.2013.6627756","url":null,"abstract":"Medical devices development and validation are difficult activities due to the critical nature of these products, involving risks to the human lives. Moreover, regulatory agencies are increasing the control over companies because of the still huge number of harms caused for several reasons, having software failures as one of the main causes. Thus it is clear that more formal and sophisticated software development techniques should be investigated. In this paper, we show how Petri nets can play the role of a generic framework for architectural decisions for control systems, allowing besides verification/simulation, an important bridge in the requested traceability by regulatory bodies. We claim that it is possible to satisfy traceability from architectural elements to code, test cases, functional and safety requirements and so on. In order to make clear our point, we conducted a case study from a generic infusion pump specification.","PeriodicalId":20519,"journal":{"name":"Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76052878","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}
Pub Date : 2013-06-20DOI: 10.1109/CBMS.2013.6627776
L. Giancardo, T. Karnowski, K. Tobin, F. Mériaudeau, E. Chaum
In recent years, automated retina image analysis (ARIA) algorithms have received increasing interest by the medical imaging analysis community. Particular attention has been given to techniques able to automate the pre-screening of Diabetic Retinopathy (DR) using inexpensive retina fundus cameras. With the growing number of diabetics worldwide, these techniques have the potential benefits of broad-based, inexpensive screening. The contribution of this paper is twofold: first, we propose a straightforward pipeline from microaneurysm (an early sign of DR) detection to automatic classification of DR without employing any additional features; then, we quantify the generalisation ability of the MA detection method by employing synthetic examples and, more importantly, we experiment with two public datasets which consist of more than 1,350 images graded as normal or showing signs of DR. With cross-datasets tests, we obtained results better or comparable to other recent methods. Since our experiments are performed only on publicly available datasets, our results are directly comparable with those of other research groups.
{"title":"Validation of microaneurysm-based diabetic retinopathy screening across retina fundus datasets","authors":"L. Giancardo, T. Karnowski, K. Tobin, F. Mériaudeau, E. Chaum","doi":"10.1109/CBMS.2013.6627776","DOIUrl":"https://doi.org/10.1109/CBMS.2013.6627776","url":null,"abstract":"In recent years, automated retina image analysis (ARIA) algorithms have received increasing interest by the medical imaging analysis community. Particular attention has been given to techniques able to automate the pre-screening of Diabetic Retinopathy (DR) using inexpensive retina fundus cameras. With the growing number of diabetics worldwide, these techniques have the potential benefits of broad-based, inexpensive screening. The contribution of this paper is twofold: first, we propose a straightforward pipeline from microaneurysm (an early sign of DR) detection to automatic classification of DR without employing any additional features; then, we quantify the generalisation ability of the MA detection method by employing synthetic examples and, more importantly, we experiment with two public datasets which consist of more than 1,350 images graded as normal or showing signs of DR. With cross-datasets tests, we obtained results better or comparable to other recent methods. Since our experiments are performed only on publicly available datasets, our results are directly comparable with those of other research groups.","PeriodicalId":20519,"journal":{"name":"Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75161711","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}
Pub Date : 2013-06-20DOI: 10.1109/CBMS.2013.6627807
Jorge Oliveira, G. Minas, Carlos Alberto Silva
The automatic detection of microaneurysms in eye fundus images can be used by medical personnel to reduce the time of analysis, permitting to cope with the high volume of exams necessary for screening the diabetic retinopathy. The goal of this work is to explore the Slant Stacking formulation of the Radon transform to automatically detect microa-neurysms on retinographies. This formulation of the Radon Transform exhibits interesting properties, namely, the invariance of the shape on the Radon domain which is explored in our proposal. The results obtained on the Di-aretDB1 with this algorithm were 89.46%, 84.16%, 84.16% for sensitivity, specificity and accuracy, respectively, while the area under the ROC was 0.83.
{"title":"Automatic detection of microaneurysm based on the slant stacking","authors":"Jorge Oliveira, G. Minas, Carlos Alberto Silva","doi":"10.1109/CBMS.2013.6627807","DOIUrl":"https://doi.org/10.1109/CBMS.2013.6627807","url":null,"abstract":"The automatic detection of microaneurysms in eye fundus images can be used by medical personnel to reduce the time of analysis, permitting to cope with the high volume of exams necessary for screening the diabetic retinopathy. The goal of this work is to explore the Slant Stacking formulation of the Radon transform to automatically detect microa-neurysms on retinographies. This formulation of the Radon Transform exhibits interesting properties, namely, the invariance of the shape on the Radon domain which is explored in our proposal. The results obtained on the Di-aretDB1 with this algorithm were 89.46%, 84.16%, 84.16% for sensitivity, specificity and accuracy, respectively, while the area under the ROC was 0.83.","PeriodicalId":20519,"journal":{"name":"Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73594025","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}
Pub Date : 2013-06-20DOI: 10.1109/CBMS.2013.6627806
S. Frade, S. M. Freire, E. Sundvall, J. Patriarca-Almeida, R. Correia
Efficiently storing and retrieving archetype-based patient information can be a challenging task. This paper surveys current archetype-based system implementations in the world and in particular the different approaches that have been used to create 13606- or openEHR-based storage repositories. Data is reported from systems with a few records to millions of records, including both deployed systems in production and experimental systems. Worldwide 21 projects were found, 4 did not reply and 1 did not provide data. Many systems (n=11) base their storage on RDBMS, then often (n=6) with some XML data fields. Dedicated XML (n=3) and object-oriented (n=2) databases were other examples of storage used. Query formalisms used include SQL, AQL, XQuery and XPath. Service interfaces via SOAP (n=12) or REST (n=6) are common. Most systems support dynamic configuration using new/changed archetypes and templates dynamically without system restart. Some (n=7) systems use demographic archetypes. In addition to the built in DBMS indexing mechanisms, one project reports use of an additional inverted index to achieve improved performance.
{"title":"Survey of openEHR storage implementations","authors":"S. Frade, S. M. Freire, E. Sundvall, J. Patriarca-Almeida, R. Correia","doi":"10.1109/CBMS.2013.6627806","DOIUrl":"https://doi.org/10.1109/CBMS.2013.6627806","url":null,"abstract":"Efficiently storing and retrieving archetype-based patient information can be a challenging task. This paper surveys current archetype-based system implementations in the world and in particular the different approaches that have been used to create 13606- or openEHR-based storage repositories. Data is reported from systems with a few records to millions of records, including both deployed systems in production and experimental systems. Worldwide 21 projects were found, 4 did not reply and 1 did not provide data. Many systems (n=11) base their storage on RDBMS, then often (n=6) with some XML data fields. Dedicated XML (n=3) and object-oriented (n=2) databases were other examples of storage used. Query formalisms used include SQL, AQL, XQuery and XPath. Service interfaces via SOAP (n=12) or REST (n=6) are common. Most systems support dynamic configuration using new/changed archetypes and templates dynamically without system restart. Some (n=7) systems use demographic archetypes. In addition to the built in DBMS indexing mechanisms, one project reports use of an additional inverted index to achieve improved performance.","PeriodicalId":20519,"journal":{"name":"Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79077840","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}
Pub Date : 2013-06-20DOI: 10.1109/CBMS.2013.6627811
J. Epstein, M. Levin, Mark S. Jowell
Preoperative evaluation is a critical skill for anesthesiologists. Training and assessing the performance of residents with standardized patients is expensive, time consuming and resource intensive. In certain cases, virtual humans may provide more fidelity than standardized patients. This technology offers a scalable, portable solution to such a problem. We created a virtual human preoperative patient interview simulator (Avatar) as a joint project between the Icahn School of Medicine at Mount Sinai (New York, NY) and LogicJunction, Inc. (Cleveland, Ohio). Users ask free-text questions as well as perform physical examination and order laboratory studies and receive feedback on their performance. We randomized a cohort of first year anesthesiology residents to perform a preoperative assessment on the Avatar or a standardized patient. While average interview time was increased with participants interviewing the Avatar, total number of questions and performance on objective feedback criteria was similar between the two groups.
{"title":"Agent based simulation for training and assessing students in the field of anesthesiology","authors":"J. Epstein, M. Levin, Mark S. Jowell","doi":"10.1109/CBMS.2013.6627811","DOIUrl":"https://doi.org/10.1109/CBMS.2013.6627811","url":null,"abstract":"Preoperative evaluation is a critical skill for anesthesiologists. Training and assessing the performance of residents with standardized patients is expensive, time consuming and resource intensive. In certain cases, virtual humans may provide more fidelity than standardized patients. This technology offers a scalable, portable solution to such a problem. We created a virtual human preoperative patient interview simulator (Avatar) as a joint project between the Icahn School of Medicine at Mount Sinai (New York, NY) and LogicJunction, Inc. (Cleveland, Ohio). Users ask free-text questions as well as perform physical examination and order laboratory studies and receive feedback on their performance. We randomized a cohort of first year anesthesiology residents to perform a preoperative assessment on the Avatar or a standardized patient. While average interview time was increased with participants interviewing the Avatar, total number of questions and performance on objective feedback criteria was similar between the two groups.","PeriodicalId":20519,"journal":{"name":"Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74131477","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}
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