SEE PAGE 988 A nimal studies on the intracoronary electrocardiogram (IC ECG) preceded coronary angioplasty, today referred to as percutaneous coronary intervention (PCI), by 1 year, almost 40 years ago (1). Even the balloon was there, but it was used for temporary coronary occlusion producing ischemia rather than for treating coronary stenoses. In 1983, pacemaker electrodes were used to derive ...

Electrocardiogram (ECG) signal processing aims basically 1) at artifact reduction to make the ECG signals cleaner and better interpretable by human or machine observers, 2) at revealing aspects not immediately observable in plain measured ECG signals even after artifact reduction, or 3) at diagnostics decision support and automated ECG signal interpretation, including classification of ECG sign...

In this paper, we propose a technique of artificial intelligence called adaptive neuro fuzzy inference system (ANFIS) for canceling maternal electrocardiogram (MECG) in fetal electrocardiogram extraction (FECG).This technique is used to estimate the MECG present in the abdominal signal of a pregnant woman. The FECG is then extracted by subtracting the estimated MECG from the abdominal signal. P...

The benefits of four-dimensional computed tomography (4D CT) are limited by the presence of artifacts that remain difficult to quantify. A correlation-based metric previously proposed for ciné 4D CT artifact identification was further validated as an independent artifact evaluator by using a novel qualitative assessment featuring a group of observers reaching a consensus decision on artifact lo...

Combined EEG/fMRI recording has been used to localize the generators of EEG events and to identify subject state in cognitive studies and is of increasing interest. However, the large EEG artifacts induced during fMRI have precluded simultaneous EEG and fMRI recording, restricting study design. Removing this artifact is difficult, as it normally exceeds EEG significantly and contains components...

Retrospective artifact correction (RAC) improves image quality post acquisition and enhances usability. Recent machine learning driven techniques for RAC are predominantly based on supervised therefore practical utility can be limited as data with paired artifact-free artifact-corrupted images typically insufficient or even non-existent. Here we show that unwanted artifacts disentangled removed...