Showing papers in "Computer Methods and Programs in Biomedicine in 2012"

TL;DR: The aim of this paper is to review, analyze and categorize the retinal vessel extraction algorithms, techniques and methodologies, giving a brief description, highlighting the key points and the performance measures.

TL;DR: This survey reviews sensors that have been used to measure stress and investigates techniques for modelling stress, and discusses non-invasive and unobtrusive sensors for measuring computed stress, a term coined in the paper.

TL;DR: An efficient automated new approach for sleep stage identification based on the new standard of the American academy of sleep medicine (AASM) is presented and features were extracted from the time-frequency representation of the EEG signal using Renyi's entropy.

TL;DR: An automated method for segmentation of blood vessels in retinal images is reported and the results demonstrate that the performance of the proposed algorithm is comparable with state of the art techniques in terms of accuracy, sensitivity and specificity.

TL;DR: An overview of the image analysis techniques in the domain of histopathology, specifically, for the objective of automated carcinoma detection and classification is presented and emphasis is given to state-of-the-art image segmentation methods for feature extraction and disease classification.

TL;DR: This paper examines the use of wavelet detail coefficients for the accurate detection of different QRS morphologies in ECG based on the power spectrum of QRS complexes in different energy levels since it differs from normal beats to abnormal ones.

TL;DR: The results show that HOS of WPC as features are highly discriminative for the classification of different arrhythmic ECG beats.

TL;DR: A new taxonomy for prostate segmentation strategies is defined that allows first to group the algorithms and then to point out the main advantages and drawbacks of each strategy, and a discussion on choosing the most appropriate segmentation strategy for a given imaging modality is provided.

TL;DR: A database is presented which is part of an EU-funded project "EPILEPSIAE" aiming at the development of seizure prediction algorithms which can monitor the EEG for seizure precursors, designed for an efficient organization, access and search of the data of 300 epilepsy patients.

TL;DR: The ability of a single wireless inertial sensing device stuck on the lower trunk to provide spatial-temporal parameters during level walking and shows promise also for a future routine clinical use is investigated.

TL;DR: A novel machine learning method that hybridizes support vector machine (SVM) and simulated annealing (SA) is proposed that is very promising with regard to the other classification methods in the literature for this problem.

TL;DR: The proposed algorithms were extensively applied on all the 322 mammogram images in MIAS database resulting in complete pectoral muscle suppression in most of the images.

TL;DR: An Integrated Index called thyroid malignancy index (TMI) made up of discrete wavelet transformation and texture features is composed to facilitate distinguishing and diagnosing benign or malignant nodules using just one index or number.

TL;DR: A system that enables processing of full resolution images, and a new algorithm for segmenting the nuclei under adequate control of the expert user are implemented, with promising results.

TL;DR: An effective paroxysmal atrial fibrillation (PAF) prediction algorithm is presented, which is based on analysis of the heart rate variability (HRV) signal, and presents better results than the other existing approaches.

TL;DR: An automated diagnosis system for DR integrated with a user-friendly interface that quantifies the severity level of DR based on detecting and analyzing the early clinical signs associated with the disease, such as microaneurysms (MAs) and hemorrhages (HAs).

TL;DR: This paper presents an R package smcure to fit the semiparametric proportional hazards mixture cure model and the accelerated failure time mixture cures model.

TL;DR: Experimental results demonstrate that the proposed generalized rough fuzzy c-means algorithm is more robust to the initialization, noise, and bias field, and can produce more accurate and reliable segmentations.

TL;DR: In this article, the authors proposed to reduce the computational load of this comparison by checking only a subset of salient features associated to the pixels, which suffice to estimate the actual difference as computed in the original NLM approach.

TL;DR: A complete segmentation system is developed for segmenting DR, including hard exudates, cotton wool spots, MAs, and HEMs, and a Naïve Bayes method is applied for segmentation of DR.

TL;DR: It is demonstrated that when the system states are not fully measurable, in conjunction with model parameter discrepancy, MPC is still a useful method for cancer treatment, through the application of moving horizon estimation (MHE), an optimisation-based method to jointly estimate the systemStates and parameters.

TL;DR: Six archetypical service categories, namely handling adverse conditions, assessing state of health, consultation and education, motivation and feedback, service ordering and social inclusion, are presented and their implementation in current research projects are described.

TL;DR: This work presents a technique able to deal with geometrically non-linear models, based on the employ of model reduction techniques, together with an efficient non- linear solver.

TL;DR: This paper presents the methodological approach followed in the design process of a web-based information system for managing the clinical information in hemophilia care, which integrates the values and practices of user-centered design activities into the principles of software engineering, particularly in the phase of requirements engineering (RE).

TL;DR: The results of this study indicate that the proposed classifiers may contribute to easy the diagnostic of COPD by using forced oscillation measurements.

TL;DR: This paper gives a review of recent numerical investigations of various configurations of coronary artery bypass grafts (CABG) and ends with a summary of the findings and the future directions.

TL;DR: This paper presents the extension of the optimal design software PopED, which incorporates many of these recent advances into an easily useable enhanced GUI and presents new solutions to problems related to the design of experiments.

TL;DR: A wireless coupled recording device that records the ECG, the blood pressure and the skin temperature and includes a 3D-acceleration sensor for the determination of the movements during recording and uses data fusion to reject or correct distorted vital sign signals.

TL;DR: iGAIT provides a user-friendly graphical interface to display and analyse gait acceleration data recorded by an accelerometer attached to the lower back of subjects, which can be used to derive 31 features from acceleration data, including 6 spatio-temporal features, 7 regularity and symmetry features, and 18 spectral features.

TL;DR: A joint encryption/watermarking algorithm for the purpose of protecting medical images that gives access to the outcomes of the image integrity and of its origins as its attachment to one patient even if the image is stored encrypted.