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Early detection of pulmonary nodules is extremely important for the diagnosis and treatment of lung cancer. In this study, a new classification approach for pulmonary nodules from CT imagery is presented by using hybrid features. Four different methods are introduced for the proposed system. The overall detection performance is evaluated using various(More)
Computer-aided detection systems can help radiologists to detect pulmonary nodules at an early stage. In this paper, a novel Computer-Aided Diagnosis system (CAD) is proposed for the classification of pulmonary nodules as malignant and benign. The proposed CAD system using ensemble learning classifiers, provides an important support to radiologists at the(More)
We explore the effect of using bagged decision tree (BDT) as an ensemble learning method with proposed time-domain feature extraction methods on electrocardiogram (ECG) arrhythmia beat classification comparing with single decision tree (DT) classifier. RR interval is the main property which defines irregular heart rhythm, and its ratio to the previous value(More)
In this work, a new signal processing method was proposed in order to predict externally applied forces to human hands by deriving a relationship between the surface electromyographic (SEMG) signals and experimentally known forces. This relationship was investigated by analyzing the spectral features of the SEMG signals. SEMG signals were recorded from(More)
We consider the estimation of time-varying channels for Cooperative Orthogonal Frequency Division Multiplexing (CO-OFDM) systems. In the next generation mobile wireless communication systems, significant Doppler frequency shifts are expected the channel frequency response to vary in time. A time-invariant channel is assumed during the transmission of a(More)
We present a fractional Gabor expansion on a general, non-rectangular time-frequency lattice. The traditional Gabor expansion represents a signal in terms of time and frequency shifted basis functions, called Gabor logons. This constant-bandwidth analysis results in a fixed, rectangular time frequency plane tiling. Many of the practical signals require a(More)
BACKGROUND Digital breast tomosynthesis (DBT) is an emerging imaging modality which produces three-dimensional radiographic images of breast. DBT reconstructs tomographic images from a limited view angle, thus data acquired from DBT is not sufficient enough to reconstruct an exact image. It was proven that a sparse image from a highly undersampled data can(More)
If the respiratory system is represented as a one compartment model composed of linear electrical elements, the Minimum Variance Unbiased Estimation (MVUE) is the optimum statistical method to estimate the model parameters. Two well known linear models, RIC and Viscoelastic models were chosen and their parameters were estimated by MVUE. Synthetic data(More)