tailieunhanh - Báo cáo hóa học: "Research Article Independent Component Analysis for Magnetic Resonance Image Analysis"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Independent Component Analysis for Magnetic Resonance Image Analysis | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 780656 14 pages doi 2008 780656 Research Article Independent Component Analysis for Magnetic Resonance Image Analysis Yen-Chieh Ouyang 1 Hsian-Min Chen 1 Jyh-Wen Chai 2 3 4 Cheng-Chieh Chen 1 Clayton Chi-Chang Chen 4 5 Sek-Kwong Poon 6 Ching-Wen Yang 7 and San-Kan Lee8 1 Department of Electrical Engineering National Chung Hsing University Taichung 402 Taiwan 2 Department of Radiology College of Medicine China Medical University Taichung 404 Taiwan 3 School of Medicine National Yang-Ming University Taipei 112 Taiwan 4 Department of Radiology Taichung Veterans General Hospital Taichung 407 Taiwan 5 Department of Medical Imaging and Radiological Science Central Taiwan University of Science and Technology Taichung 406 Taiwan 6 Division of Gastroenterology Department of Internal Medicine Center of Clinical Informatics Research Development Taichung Veterans General Hospital Taichung 407 Taiwan 7 Computer Center Taichung Veterans General Hospital Taichung 407 Taiwan 8Chia-Yi Veterans Hospital Chia-Yi600 Taiwan Correspondence should be addressed to Clayton Chi-Chang Chen ccc@ Received 11 October 2007 Revised 21 December 2007 Accepted 30 December 2007 Recommended by Chein-I Chang Independent component analysis ICA has recently received considerable interest in applications of magnetic resonance MR image analysis. However unlike its applications to functional magnetic resonance imaging fMRI where the number of data samples is greater than the number of signal sources to be separated a dilemma encountered in MR image analysis is that the number of MR images is usually less than the number of signal sources to be blindly separated. As a result at least two or more brain tissue substances are forced into a single independent component IC in which none of these brain tissue substances can be discriminated from another. In addition since the ICA is .