On Tue, 8 Jan 2002, Herbert Voss wrote:
> \usepackage[authoryear,square]{natbib}
Well, I finally bothered to RTFM, and did something like:
\usepackage[square]{natbib}
\renewcommand{\cite}{\citep}
This brought me the old apalike citation style back. Maybe there is a more
elegant way to tell Lyx to use \citep instead of \cite?
The natbib package knows two citation modes: text and parentheses. They
are implemented by the \citet and \citep modes respectively. \cite
appearantly defaults to the text mode
Unfortunately, while use of the natbib package reduced the number of
overfull hboxes significantly, they do still occur (see enclosed example,
the error in spelling is inteded to create a problematic situation in
terms of line length). Any simple way to further improve things? If there
is not, I think I can live with what I have now.
Thank you very much for your fast and competent help, Herbert!
Jan
#LyX 1.1 created this file. For more info see http://www.lyx.org/
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Several descriptions of brain segmentation algorithms have been publishe
\begin_inset LatexCommand \cite{schnack.2001:automated}
\end_inset
.
Most commonly, voxels are assigned to either of three tissue types: white
matter, gray matter or cerebrospinal fluid\SpecialChar \ldots{}
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\begin_inset LatexCommand \BibTeX[apalike]{bib_problem}
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% Sixpack 0.99(=0.0.6)
% Bibliography: /gaia_3/warnking/lyxdocs/tmp/bib_problem.bib
% Corresponding sixpack database: /gaia_3/warnking/lyxdocs/tmp/bib_problem.bib.bref
% created by Jan Warnkin on Tue Jan 8 17:19:13 WET 2002
% #entries: 1 1
%
@article{schnack.2001:automated,
author = { H. G. Schnack and Hulshoff Pol, H. E. and W. F. Baare and
W. G. Staal and M. A. Viergever and R. S. Kahn },
title = { {A}utomated separation of gray and white matter from {MR}
images
of the human brain. },
journal = {Neuroimage},
volume = 13,
number = 1,
pages = { 230-7 },
month = jan,
year = 2001,
keywords = { Adult Brain/*anatomy & histology/pathology Calibration Female
Human Image Processing, Computer-Assisted Magnetic Resonance
Imaging Male Middle Age Reproducibility of Results
Schizophrenia/pathology },
affiliation = { Department of Psychiatry, A01.126, University Medical Center
Utrecht, The Netherlands. },
abstract = { A simple automatic procedure for segmentation of gray and
white matter in high resolution 1.5T T1-weighted MR human
brain images was developed and validated. The algorithm
is based on histogram shape analysis of MR images that were
corrected for scanner nonuniformity. Calibration and
validation
was done on a set of 80 MR images of human brains. The
automatic
method's values for the gray and white matter volumes were
compared with the values from thresholds set twice by the
best three of six raters. The automatic procedure was shown
to perform as good as the best rater, where the average
result of the best three raters was taken as reference.
The method was also compared with two other histogram-based
threshold methods, which yielded comparable results. The
conclusion of the study thus is that automated threshold
based methods can separate gray and white matter from MR
brain images as reliably as human raters using a thresholding
procedure. Copyright 2001 Academic Press. },
file = { processingIRMs/Schnack_NIMG_01_automatedsegmentation.pdf },
url = { http://www.idealibrary.com/links/doi/10.1006/nimg.2000.0669 },
annote = { on file: processingIRMs }
}
