Improving PET Receptor Binding Estimates from Logan Plots Using Principal Component Analysis
نویسندگان
چکیده
منابع مشابه
Improving PET receptor binding estimates from Logan plots using principal component analysis.
This work reports a principal component analysis (PCA)-based approach for reducing bias in distribution volume ratio (DVR) estimates from Logan plots in positron emission tomography (PET). Comparison has been made of all existing bias-removal methods with the proposed PCA method, for both single-estimate PET studies and intervention studies where pre- and post-intervention estimates are made. B...
متن کاملImproving Class Separation in Principal Component Analysis Using Delta Analysis
A method of generating complementary eigenspaces optimised for inter-class and intra-class separability respectively is presented. The objective of creating these spaces is to improve the efficiency of eigenspace search algorithms. The inter-class optimised space may also be used to improve classification and a quantitative evaluation of this against conventional Principal Component Analysis an...
متن کاملImproving Sparse Representation-Based Classification Using Local Principal Component Analysis
Sparse representation-based classification (SRC), proposed by Wright et al., seeks the sparsest decomposition of a test sample over the dictionary of training samples, with classification to the most-contributing class. Because it assumes test samples can be written as linear combinations of their same-class training samples, the success of SRC depends on the size and representativeness of the ...
متن کاملStatistics using R (spring of 2017) Computer lab: Multivariate Plots, Principal Component Analysis and Discriminant Analysis
Consider a data matrix X of real numbers with n rows and k columns. We view the rows X1, . . . ,Xn as independent samples from a multivariate distribution with mean vector μ and covariance matrix Σ. Can we visualize X in some easy way? One possibility is to use heat plots (also known as heat maps). These are constructed as follows: think of a rectangular matrix in which column (or row) standard...
متن کاملdemonstrating buried channels using principal component analysis
spectral decomposition of time series has a significant role in seismic data processing and interpretation. since the earth acts as a low-pass filter, it changes frequency content of passing seismic waves. conventional representing methods of signals in time domain and frequency domain cannot show time and frequency information simultaneously. time-frequency transforms upgraded spectral decompo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Cerebral Blood Flow & Metabolism
سال: 2007
ISSN: 0271-678X,1559-7016
DOI: 10.1038/sj.jcbfm.9600584