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Due to the growing pace of life, stress became one of the major factors causing health problems. We have developed a framework for measuring stress in real-life conditions continuously and unobtrusively. In order to provide meaningful, useful and actionable information, we present stress information, derived from sensor measurements, in the context of person's activities. In this paper, we describe...
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...
We present results from a study of information needs when teleconsultation is used in trauma resuscitation. Three trauma team training sessions including 14 patient cases were observed together with field studies at emergency units. Technology probes like headcams and visualization of data usually available in the trauma room were used to better understand what information that is important or not...
This paper focuses on evaluating a method for measuring the retinal vessel widths in a recently publicly available database (REVIEW). The algorithm is based on deformable models and it constitutes an essential step in a methodology to compute the AVR automatically. This methodology is part of a web-based framework aimed to integrate diverse techniques in the field of retinal image analysis. The results...
We investigate the task of breast tumor classification based on dynamic contrast-enhanced magnetic resonance image data (DCE-MRI). Our objective is to study how the formation of regions of similar voxels contributes to distinguishing between benign and malignant tumors. First, we perform clustering on each tumor with different algorithms and parameter settings, and then combine the clustering results...
This paper describes the design and development of a training system for minimally invasive surgery skills in the field of otolaryngology. The main purpose of the system is for the surgical residents to gain experience and practice. In order to provide the surgeon a practical interaction environment, training modules and an evaluation methodology are proposed. The methodology consists of a series...
The increasing adoption of medical imaging equipment in healthcare has been leading to a huge dispersion of data repositories and institutions. Although the quality of diagnostic and treatment is deeply dependent on the health information that is available for physicians, several legal and technological issues have hindered the integration of these data. One of such problems is because traditional...
Fundus imaging is the most commonly used modality to collect information about the human eye background. Objective and quantitative assessment of quality for the acquired images is essential for manual, computer-aided and fully automatic diagnosis. In this paper, we present a no-reference quality metric to quantify image noise and blur and its application to fundus image quality assessment. The proposed...
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...
Many studies have been performed in predicting periodontal diseases based on genetic information, dental images or patients habits but few have yet used dental visits records. This paper proposes a methodology based on Random Forest to classify the periodontal disease condition of patients and a way to assess the most important features that lead to a successful classification. We investigate three...
Public health data could be used to assist with public health surveillance and decision support. However, in most cases data has to be transformed into a coded format to make it computable and amiable to quasi real time analytical processing. Natural language processing (NLP) systems, which aim to accurately extract and encode biomedicai information in a Standardformat, have a great potential in surveillance...
The analysis of nerve structures in the cornea subbasal epithelium is of relevant clinical interest, as it provides information related to changes caused by surgical interventions, transplantation or diseases (i.e. diabetic neuropathy). We addressed the problem of recognizing and tracing corneal nerves in confocal microscopy images with a novel method based on a sparse tracking scheme. After a set...
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,...
Intrapartum fetal heart rate monitoring constitutes an important stake aiming at early acidosis detection. Measuring heart rate variability is often considered a powerful tool to assess the intrapartum health status of fetus and has been envisaged using various techniques. In the present contribution, scale invariance parameters, such as the Hurst exponent and the global regularity exponent, are estimated...
Interlaced scanning is a technique that has been widely in use to double the perceived frame rate without increasing the used bandwidth. Interlaced scanning is still in use by endoscopic video hardware today. Towards the development of an automated decision support system we focus on the evaluation of the impact of de-interlacing techniques on the accuracy of automated classification of endoscopic...
Medical devices are increasingly capable of interacting with each other by leveraging network connectivity and interoperability, promising a great benefit for patient safety and effectiveness of medical services. However, ad-hoc integration of medical devices through networking can significantly increase the complexity of the system and make the system more vulnerable to potential errors and safety...
With the digitisation of off-line processes in e-commerce and moves towards the digitisation of consent processes in health care, the need for effective on-line consent management has grown considerably. Yet, contemporary constructs in information systems are unreportedly incomplete. For instance, the focus in contemporary literature is on the flawed notion that consent decision-making is synonymous...
This paper describes our study of the incidence of Personal Health Information (PHI) on the Web. PHI is usually shared under conditions of confidentiality, protection and trust, and should not be disclosed or available to unrelated third parties or the general public. We first analyzed the characteristics that potentially make systems successful in identification of unsolicited or unjustified PHI...
The morphometric analysis of myelinated fibers is known to produce relevant information for the evaluation of several phenomena, which range from nerve demyelization/remyelization to the aging process. This analysis can be achieved manually or using computer-based image analysis systems which vary to a certain degree of automation. However, systems which are manual or semi-automated are extremely...
AudioSense integrates mobile phones and web technology to measure hearing aid performance in real-time and in-situ. Measuring the performance of hearing aids in the real world poses significant challenges as it depends on the patient's listening context. AudioSense uses Ecological Momentary Assessment methods to evaluate both the perceived hearing aid performance as well as to characterize the listening...
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