Name
Title | ||
|---|---|---|
Exploring the complementarity of THz pulse imaging and DCE-MRIs: Toward a unified multi-channel classification and a deep learning framework. |
Abstract | ||
|---|---|---|
•The complementarity of THz transient imaging spectrometry and DCE MRI datasets for assessing disease proliferation is explained.•Multi-channel signal processing for de-noising, feature extraction and selection, as well as fusion are discussed.•Recent advances in capturing textural information for both sensing modalities are placed in context.•The general structure of multi-dimensional classifiers using complex extensions of SVM and ELM as well as Clifford algebras are explained.•Multi-layer deep-learning architectures and the use of geometric neurons are proposed for the assessment of disease proliferation in the future. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.cmpb.2016.08.026 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
THz imaging,MRI,Wavelet analysis,Complex extreme learning machine,Deep learning | Data mining,Feature selection,Extreme learning machine,Computer science,Artificial intelligence,Deep learning,Multiclass classification,Computer vision,Data structure,Support vector machine,Feature extraction,Statistical signal processing,Machine learning | Journal |
Volume | ISSN | Citations |
137 | 0169-2607 | 0 |
PageRank | References | Authors |
0.34 | 61 | 5 |