Various diseases are diagnosed using medical imaging used for analysing internal anatomical structures. However, medical images are susceptible to noise introduced in both acquisition and transmission processes. We propose an adaptive data-driven image denoising algorithm based on an improvement of the intersection of confidence intervals (ICI), called relative ICI (RICI) algorithm. The 2D mask of […]
Laboratory for Information Processing and Pattern Recognition
Mirroring Quasi-Symmetric Organ Observations for Reducing Problem Complexity
Following an obvious growth of available collections of medical images in recent years, both in number and in size, machine learning has nowadays become an important tool for solving various image-analysis-related problems, such as organ segmentation or injury/pathology detection. The potential of learning algorithms to produce models having good generalisation properties is highly dependent on […]
A Fast Signal Denoising Algorithm Based on the LPA-ICI Method for Real-Time Applications
We propose a new algorithm for denoising of additive white Gaussian noise-corrupted signals, based on the intersection of confidence intervals (ICI) algorithm, called the fast intersection of confidence intervals (FICI) algorithm. The proposed approach combines the FICI algorithm, used for the adaptive filter support size selection, with the local polynomial approximation (LPA) method, used as […]
Algorithm Based On the Short-Term Rényi Entropy And IF Estimation For Noisy EEG Signals Analysis
Stochastic electroencephalogram (EEG) signals are known to be nonstationary and often multicomponential. Detecting and extracting their components may help clinicians to localize brain neurological dysfunctionalities for patients with motor control disorders due to the fact that movement-related cortical activities are reflected in spectral EEG changes. A new algorithm for EEG signal components detection from its […]
Improved LPA-ICI-Based Estimators Embedded in a Signal Denoising Virtual Instrument
Adaptive filters embedded in a user-friendly virtual instrument (VI) for signal denoising are proposed in the paper. The filters are based on the local polynomial approximation (LPA) and equipped with the improved intersection of confidence intervals (ICI) rule, known as the relative intersection of confidence intervals (RICI) rule, in order to achieve adaptivity to high […]
