Principal Components Analysis In Medical Imaging

J. B. Weaver; A. L. Huddleston

doi:10.1117/12.975376

12 June 1986 Principal Components Analysis In Medical Imaging

J. B. Weaver, A. L. Huddleston

Proceedings Volume 0626, Application of Optical Instrumentation in Medicine XIV and Picture Archiving and Communication Systems; (1986) https://doi.org/10.1117/12.975376
Event: Application of Optical Instrumentation in Medicine XIV and Picture Archiving and Communication Systems (PACS IV) for Medical Applications, 1986, Newport Beach, CA, United States

Abstract

Principal components analysis, PCA, is basically a data reduction technique. PCA has been used in several problems in diagnostic radiology: processing radioisotope brain scans (Ref.1), automatic alignment of radionuclide images (Ref. 2), processing MRI images (Ref. 3,4), analyzing first-pass cardiac studies (Ref. 5) correcting for attenuation in bone mineral measurements (Ref. 6) and in dual energy x-ray imaging (Ref. 6,7). This paper will progress as follows; a brief introduction to the mathematics of PCA will be followed by two brief examples of how PCA has been used in the literature. Finally my own experience with PCA in dual-energy x-ray imaging will be given.

Citation Download Citation

J. B. Weaver and A. L. Huddleston "Principal Components Analysis In Medical Imaging", Proc. SPIE 0626, Application of Optical Instrumentation in Medicine XIV and Picture Archiving and Communication Systems, (12 June 1986); https://doi.org/10.1117/12.975376

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