Michael Vasilakakis

Michael Vasilakakis
University of Thessaly | UTH · Department of Computer Science and Biomedical Informatics

Computer & Communication Engineering

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17
Publications
1,247
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245
Citations

Publications

Publications (17)
Chapter
The detection of abnormalities in the gastrointestinal (GI) tract, including precancerous lesions, is substantially subject to expert knowledge and experience. To address the challenge of automated lesion risk assessment, based on Wireless Capsule Endoscopy (WCE) images, this paper introduces a novel Artificial Intelligence (AI) framework based on...
Chapter
Depression is a common and serious medical disorder that negatively affects the mood and the emotions of people, especially adolescents. In this paper, a novel framework for automatically creating Fuzzy Cognitive Maps (FCMs) is proposed. It is applied for the estimation of the severity of depression among adolescents, based on their electroencephal...
Chapter
Full-text available
Wireless capsule endoscopy (WCE) constitutes a medical imaging technology developed for the endoscopic exploration of the gastrointestinal (GI) tract, whereas it provides a more comfortable examination method, in comparison to the conventional endoscopy technologies. In this paper, we propose a novel Explainable Fuzzy Bag-of-Words (XFBoW) feature e...
Chapter
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The early detection of Heart Disease (HD) and the prediction of Heart Failure (HF) via telemonitoring and can contribute to the reduction of patients’ mortality and morbidity as well as to the reduction of respective treatment costs. In this study we propose a novel classification model based on fuzzy logic applied in the context of HD detection an...
Article
Full-text available
Several studies have addressed the problem of abnormality detection in medical images using computer-based systems. The impact of such systems in clinical practice and in the society can be high, considering that they can contribute to the reduction of medical errors and the associated adverse events. Today, most of these systems are based on binar...
Article
Full-text available
Capsule endoscopy (CE) is indicated as a first-line clinical examination for the detection of small-bowel pathology, and there is an ever-growing drive for it to become a method for the screening of the entire gastrointestinal tract (GI). Although CE's main function is diagnosis, the research for therapeutic capabilities has intensified to make the...
Article
Introduction: This review presents noteworthy advances in clinical and experimental Capsule Endoscopy (CE), focusing on the progress that has been reported over the last five years since our previous review on the subject. Areas covered: This study presents the commercially available CE platforms, as well as the advances made in optimizing the diag...
Article
Full-text available
Wireless Capsule Endoscopy (WCE) is a noninvasive diagnostic technique enabling the inspection of the whole gastrointestinal (GI) tract by capturing and wirelessly transmitting thousands of color images. Proprietary software “stitches” the images into videos for examination by accredited readers. However, the videos produced are of large length and...
Article
Full-text available
This paper proposes a novel methodology for automatic detection and localization of gastrointestinal (GI) anomalies in endoscopic video frame sequences. Training is performed with weakly annotated images, using only image-level, semantic labels instead of detailed, pixel-level annotations. This makes it a cost-effective approach for the analysis of...
Conference Paper
Several computer-based medical systems have been proposed for automatic detection of abnormalities in a variety of medical imaging domains. The majority of these systems are based on binary supervised classification algorithms capable of discriminating abnormal from normal image patterns. However, this approach usually does not take into account th...
Conference Paper
Robotic video capsule endoscopy (VCE) is a rapidly evolving medical imaging technology enabling more thorough examination and treatment of the gastrointestinal tract than conventional endoscopy technologies. Despite of the technological advances in this field, the reviewing of the large VCE image sequences remains manual and challenges experts’ dia...
Conference Paper
Graphic image annotations provide the necessary ground truth information for supervised machine learning in image-based computer-aided medical diagnosis. Performing such annotations is usually a time-consuming and cost-inefficient process requiring knowledge from domain experts. To cope with this problem we propose a novel weakly-supervised learnin...

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