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...

one of the most fundamental features of digital image and the basic steps in image processing, analysis, pattern recognition and computer vision is the edge of an image where the preciseness and reliability of its results will affect directly on the comprehension machine system made objective world. several edge detectors have been developed in the past decades, although no single edge detector...

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...

For decades, IS researchers have discussed the reliability of subjective measurements to assess actual artifact usage. Especially in experimental settings, as in the design science context for instance, the participants’ usage data of the evaluated artifact represents an important point of analysis. However, collecting objective usage data, (i.e. logfiles) is often not feasible depending on the...