By Fabian J. Theis
A finished advent to leading edge equipment within the box of biomedical sign research, protecting either conception and perform.
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Extra info for Biomedical Signal Analysis: Contemporary Methods and Applications
The methods employed for removing redundant information are exhaustive, heuristic, or nondeterministic. 16 Typical architecture of a CAD workstation. • Classiﬁcation of the selected ROI: Classiﬁcation, either supervised or unsupervised, assigns a given set of features describing the ROI to its proper class. These classes can be in medical imaging of tumors, diseases, or physiological signal groups. Several supervised and unsupervised classiﬁcation algorithms have been applied in the context of breast tumor diagnosis [171, 201, 294].
The imaging equation in PET is similar to that in SPECT, with one diﬀerence: The limits of integration for the 16 Chapter 1 attenuation term span the entire body because of the coincidence detection of paired γ-rays, the so-called annihilation photons. 9) −R where K represents a constant that includes the constant factors, such as detector area and eﬃciency, that inﬂuence ϕ. The image quality in both SPECT and PET is limited by resolution, scatter, and noise. PET has its main clinical application in oncology, neurology, and psychiatry.
They provide enhanced processing capabilities compared to the traditional ones in terms of denoising, compression, enhancement, and edge and feature extraction. These techniques fall under the categories of multiresolution analysis, time-frequency analysis, or pyramid algorithms. The wavelet transform is based on wavelets, which are small waves of varying frequency and limited duration, and thus represents a deviation from the traditional Fourier transform concept that has sinusoids as basis functions.
Biomedical Signal Analysis: Contemporary Methods and Applications by Fabian J. Theis