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We report, as part of the EMBC meeting Cognitive State Assessment (CSA) competition 2011, an empirical comparison using robust cross-validation of the performance of eleven computational approaches to real-time electroencephalography (EEG) based mental workload monitoring on Multi-Attribute Task Battery data from eight subjects. We propose a new approach, Overcomplete Spectral Regression, that combines...
A new methodology to automatically extract features from mammograms and classify them is presented. It relies on a hybrid processing system that sequentially uses the discrete cosine transform (DCT) to obtain the high frequency component of the mammogram and then applies the Radon transform to the obtained DCT image in order to extract its directional features. The features are subsequently fed to...
Cardiotocography (CTG) is the monitoring of fetal heart rate (FHR) and uterine contractions (TOCO) since 1960's used routinely by obstetricians to detect fetal hypoxia. The evaluation of the FHR in clinical settings is based on an evaluation of macroscopic morphological features and so far has managed to avoid adopting any achievements from the HRV research field. In this work, most of the ever-used...
Cardiac auscultation has proven to be an excellent diagnostic tool. Heart sound processing algorithms are not completely robust in the presence of noise, requiring clean segments of heart sounds to extract reliable diagnostic features. This paper presents a new approach to detect transient noises mixed with heart sound. The algorithm explores a single channel source separation algorithm and evaluates...
Lower-limb prostheses are rapidly advancing with greater computing power and sensing modalities. This paper is an attempt to begin exploring the trade-off between extrinsic and intrinsic control modalities. In this case, between electromyographic (extrinsic) and several internal sensors that can be used for intrinsic control. We propose a method that will identify the particular features, taken from...
This paper introduces ongoing research on computer-aided ophthalmic surgery. In particular, a novel Content-Based Video Retrieval (CBVR) system is presented. Its purpose is the following: given a video stream captured by a digital camera monitoring the surgery, the system should retrieve, in real-time, similar video subsequences in video archives. In order to retrieve semantically-relevant videos,...
Quantitative characterization of carotid atherosclerosis and classification into either symptomatic or asymptomatic is crucial in terms of diagnosis and treatment planning for a range of cardiovascular diseases. This paper presents a computer-aided diagnosis (CAD) system (Atheromatic™, patented technology from Biomedical Technologies, Inc., CA, USA) which analyzes ultrasound images and classifies...
In this paper, we present a blind forensic approach for the detection of global image modifications like filtering, lossy compression, scaling and so on. It is based on a new set of image features we proposed, called Histogram statistics of Reorganized Block-based Tchebichef moments (HRBT) features, and which are used as input of a set of classifiers we learned to discriminate tampered images from...
Optical Coherence Tomography (OCT) is a fiber — optic imaging modality which produces high resolution tomographic images of the coronary lumen and outer vessel wall. While OCT images present morphological information in highly resolved detail, the characterization of the various plaque components relies on trained readers. The aim of this study is to extract a set of features in grayscale OCT images...
Brain Computer Interface (BCI) systems control the user's environment via his/her brain signals. Brain signals related to motor imagery (MI) have become a widespread method employed by the BCI community. Despite the large number of references describing the MI signal treatment, there is not enough information related to the available programming languages that could be suitable to develop a specific-purpose...
The analysis of isometric force may provide early detection of certain types of neuropathology such as Parkinson's disease. Our long term goal is to determine if there are detectable differences between model parameters of healthy verses unhealthy individuals. As a first step toward our long-term goal, we studied 24 healthy young adults ages 18 through 24 years, both male and female. The experiments...
Retinal image has been considered for number of health and biometrics applications. However, the reliability of these has not been investigated thoroughly. The variation observed in retina scans taken at different times is attributable to differences in illumination and positioning of the camera. It causes some missing bifurcations and crossovers from the retinal vessels. Exhaustive selection of optimal...
3D functional neuroimaging is used in the diagnosis and management of neurological disorders. The efficient management and analysis of these large imaging datasets has prompted research in the field of content-based image retrieval. In this context, our generalized regional disorder-sensitive-weighting (DSW) scheme gives greater weight to brain regions affected by the diseases than regions that are...
The respiratory rate is a vital sign that can provide important information about the health of a patient, especially that of the respiratory system. The aim of this study is to develop a simple method that can be applied in wearable systems to monitor the respiratory rate automatically and continuously over extended periods of time. In this paper, a novel respiratory rate estimation method is presented...
We investigate the use of machine learning methods based on the pre-treatment electroencephalograph (EEG) to predict response to repetitive transcranial magnetic stimulation (rTMS), which is a non-pharmacological form of therapy for treating major depressive disorder (MDD). The learning procedure involves the extraction of a large number of candidate features from EEG data, from which a very small...
Orthodontic craniometric landmarks provide critical information in oral and maxillofacial imaging diagnosis and treatment planning. The Dent-landmark, defined as the odontoid process of the epistropheus, is one of the key landmarks to construct the midsagittal reference plane. In this paper, we propose a learning-based approach to automatically detect the Dent-landmark in the 3D cone-beam computed...
This paper presents a statistical image modeling approach based on Markov random field to synthesize cervical tissue second harmonic generation (SHG) images. Binary images representing fiber and pore areas of the cervix tissue are first obtained from SHG images using an image processing pipeline consisting of noise removal, contrast enhancement and optimal thresholding. These binary images are modeled...
Advances in medical imaging and screening tests have made possible the detection and diagnosis of many diseases in their early stages. Those advances have enabled more effective planning, execution, and monitoring of a treatment plan. However, early detection has also resulted in an increase of the number of longitudinal radiographs requested for most patients, thus increasing the risk for potential...
The pace of technology has allowed classification of feature-subset of methylated and unmethylated of CpG islands of DNA sequence properties. As methylation of CpG islands is involved in various biological phenomena and function of the DNA methylation is correlated to various human diseases such as cancer, analysis of the CpG islands has become important and useful in characterizing and modelling...
A methodology for wavelet synthesis based on lifting scheme and genetic algorithms is presented. Often, the wavelet synthesis is addressed to solve the problem of choosing properly a wavelet function from an existing library, but which may be not specially designed to the application in hand. The task under consideration is the identification of epileptic seizures over electroencephalogram recordings...
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