2016
Authors
Goncalves, L; Novo, J; Campilho, A;
Publication
IMAGE ANALYSIS AND RECOGNITION (ICIAR 2016)
Abstract
In this paper, a Hessian-based strategy, based on the central medialness adaptive principle, was adapted and proposed in a multiscale approach for the 3D segmentation of pulmonary nodules in chest CT scans. This proposal is compared with another well stated Hessian based strategy of the literature, for nodule extraction, in order to demonstrate its accuracy. Several scans from the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) database were employed in the test and validation procedure. The scans include a large and heterogeneous set of 569 solid and mostly solid nodules with a large variability in the nodule characteristics and image conditions. The results demonstrated that the proposal offers correct results, similar to the performance of the radiologists, providing accurate nodule segmentations that perform the desirable scenario for a posterior analysis and the eventual lung cancer diagnosis.
2016
Authors
Rouco, J; Azevedo, E; Campilho, A;
Publication
SENSORS
Abstract
This article describes a method that improves the performance of previous approaches for the automatic detection of the common carotid artery (CCA) lumen centerline on longitudinal B-mode ultrasound images. We propose to detect several lumen centerline candidates using local symmetry analysis based on local phase information of dark structures at an appropriate scale. These candidates are analyzed with selection mechanisms that use symmetry, contrast or intensity features in combination with position-based heuristics. Several experimental results are provided to evaluate the robustness and performance of the proposed method in comparison with previous approaches. These results lead to the conclusion that our proposal is robust to noise, lumen artifacts, contrast variations and that is able to deal with the presence of CCA-like structures, significantly improving the performance of our previous approach, from [GRAPHICS] of correct detections to [GRAPHICS] in a set of 200 images.
2016
Authors
Teles, AS; Silva, FJ; Rocha, A; Lopes, JC; O'Sullivan, D; Van de Ven, P; Endler, M;
Publication
2016 IEEE 29TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS)
Abstract
This work describes SituMan (Situation Manager), a mobile system that makes use of the sensors commonly included in most mobile platforms and a fuzzy inference engine to attempt to infer user context and environment. Such "situation" information, has been used to enhance the behaviour of MoodBuster, another mobile application used in the scope of the mental health domain to collect Ecological Momentary Assessments (EMA). EMA has been used in psychotherapy to minimize the effects of recall bias in the assessment of patient mood, as well as in the recollection of other experiences and behaviours. SituMan can enhance the user experience in the scope of EMA by prompting users in the desired situation, instead of at random or fixed-times, thus reducing obtrusiveness. It can also provide new insight to mental health professionals by summarizing the situations experienced by the patient, further allowing correlation of situation information with patient mood within the same time frame.
2016
Authors
Vilas Boas, MDC; Cunha, JPS;
Publication
IEEE Reviews in Biomedical Engineering
Abstract
The movement of the human body offers neurologists important clues for the diagnosis and follow-up of many neurological diseases. The typical diagnosis approach is accomplished through simple observation of movements of interest (MOI) associated with a specific neurological disease. This approach is highly subjective because it is mainly based on qualitative evaluation of MOIs. Quantitative movement techniques are then obvious diagnosis-aid systems to approach these cases. Nevertheless, the use of motion quantification techniques in these pathologies is still relatively rare. In this paper, we intend to review this area and provide a clear picture of the current state of the art, both in the methods used and their applications to the main movement-related neurological diseases. We approach some historic aspects and the current state of the motion capture techniques and present the results of a survey to the literature that includes 82 papers, since 2006, covering the usage of these techniques in neurological diseases. Furthermore, we discuss the pros and cons of using quantitative approaches in these clinical scenarios. Finally, we present some conclusions and discuss the trends we foresee for the future. © 2008-2011 IEEE.
2016
Authors
Paiva, JS; Rodrigues, S; Silva Cunha, JPS;
Publication
2016 38TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Abstract
Firefighting is a stressful occupation. The monitoring of psychophysiological measures in those professionals can be a way to prevent and early detect cardiac diseases and other stress-related problems. The current study aimed to assess morphological changes in the ECG signal induced by acute stress. A laboratory protocol was conducted among 6 firefighters, including a laboratory stress-inducer task - the Trier Social Stress Task (TSST) - and a 2-choice reaction time task (CRTT) that was performed before (CRTT1) and after (CRTT2) the stress condition. ECG signals were continuously acquired using the VitalJacket (R), a wearable t-shirt that acts as a medical certified ECG monitor. Results showed that ECG morphological features such as QT and ST intervals are able to differentiate stressful from non stressful events in first responders. Group mean Visual Analogue Scale (VAS) for stress assessment significantly increased after the stress task (TSST), relatively to the end of CRTT2 (after TSST: 4.67 +/- 1.63; after CRTT2: 3.17 +/- 0.75), a change that was accompanied by a significant increase in group mean QT and ST segments corrected for heart rate during TSST. These encouraging results will be followed by larger studies in order to explore those measures and its physiological impact under realistic environments in a higher scalability.
2016
Authors
Sequeira A.F.; Chen L.; Ferryman J.; Alonso-Fernandez F.; Bigun J.; Raja K.B.; Raghavendra R.; Busch C.; Wild P.;
Publication
Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)
Abstract
This work presents a novel dual-spectrum database containing both iris and periocular images synchronously captured from a distance and within a realistic indoor environment. This database was used in the 1st Cross-Spectrum Iris/Periocular Recognition Competition (Cross-Eyed 2016). This competition aimed at recording recent advances in cross-spectrum iris and periocular recognition. Six submissions were evaluated for crossspectrum periocular recognition, and three for iris recognition. The submitted algorithms are briefly introduced. Detailed results are reported in this paper, and comparison of the results is discussed.
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