From 6b025a4e77ffb41f3584a48ce8b7604bf249ecc4 Mon Sep 17 00:00:00 2001
From: Stephen Smith <steve@fmrib.ox.ac.uk>
Date: Fri, 17 Sep 2004 12:20:35 +0000
Subject: [PATCH] *** empty log message ***

---
 doc/index.html | 77 ++++++++++++++++++++++++++++++++++++++------------
 1 file changed, 59 insertions(+), 18 deletions(-)

diff --git a/doc/index.html b/doc/index.html
index 8319c3e..d4e7d91 100644
--- a/doc/index.html
+++ b/doc/index.html
@@ -4,16 +4,19 @@
 <TITLE>SIENA - Structural Brain Change Analysis</TITLE>
 </HEAD><BODY BACKGROUND="../images/fsl-bg.jpg">
 <hr><TABLE BORDER=0 WIDTH="100%"><TR>
-<TD ALIGN=CENTER><H1>SIENA Structural Brain Change Analysis<br>User
-Guide<br></H1>(SIENA - Structural Image Evaluation, using
-Normalisation, of Atrophy - Version 2.2)
+<TD ALIGN=CENTER><H1>SIENA Structural Brain Change Analysis</H1>
+SIENA - Structural Image Evaluation, using Normalisation, of Atrophy - Version 2.3<br><br>
+
+<a href="#intro">intro</a> - <a href="#tools">tools used</a> - <a href="#siena">SIENA</a> - <a
+href="#sienax">SIENAX</a> - <a href="#sienar">voxelwise SIENA statistics</a>
+
 <TD ALIGN=RIGHT><a href="../index.html"><IMG BORDER=0 SRC="../images/fsl-logo.jpg"></a>
 </TR></TABLE>
 
 <!-- }}} -->
 <!-- {{{ Introduction -->
 
-<hr><H2>Introduction</H2>
+<a name="intro"></a><p><hr><H2>Introduction</H2>
 
 <p>SIENA is a package for both single-time-point ("cross-sectional")
 and two-time-point ("longitudinal") analysis of brain change, in
@@ -50,7 +53,7 @@ references listed there.
 <!-- }}} -->
 <!-- {{{ FSL Tools used -->
 
-<hr><H2>FSL Tools used</H2>
+<a name="tools"></a><p><hr><H2>FSL Tools used</H2>
 
 This section lists the generic FSL programs that SIENA uses.
 
@@ -83,9 +86,9 @@ important to choose the right option here, depending on whether there
 is or is not reasonable grey-white contrast in the image.
 
 <!-- }}} -->
-<!-- {{{ Two-Time-Point Estimation -->
+<!-- {{{ SIENA - Two-Time-Point Estimation -->
 
-<hr><H2>Two-Time-Point Estimation</H2>
+<a name="siena"></a><p><hr><H2>SIENA - Two-Time-Point Estimation</H2>
 
 <h3>Usage</h3>
 
@@ -94,9 +97,9 @@ href="siena_usage">usage</a>) is run simply by typing
 
 <p><b>siena &lt;input1_fileroot&gt; &lt;input2_fileroot&gt;</b>
 
-<p>where the two input fileroots are analyze images without the .hdr
-or .img extensions. Note that the input fileroot must not contain
-directory names - i.e. all must be done within a single directory.
+<p>where the two input fileroots are images without any filename
+extensions. Note that the input fileroot must not contain directory
+names - i.e. all must be done within a single directory.
 
 <p>Other options are:
 
@@ -109,6 +112,8 @@ and vice versa
 <p><b>-2</b> : two-class segmentation (don't segment grey and white
 matter separately) - use this if there is poor grey/white contrast
 
+<p><b>-t2</b>: tell FAST that the input images are T2-weighted and not T1
+
 <p><b>-m</b> : use Talairach-space masking as well as BET (e.g. if it
 is proving hard to get reliable brain segmentation from BET, for
 example if eyes are hard to segment out) - register to Talairach space
@@ -200,7 +205,7 @@ images are called "A" and "B"):
 
 <LI>A_to_B.siena the output information from the <b>siena</b> script.
 
-<LI>A_halfwayto_B_render.hdr a colour rendered image of edge motion
+<LI>A_halfwayto_B_render a colour rendered image of edge motion
 superimposed on the halfway A image.
 
 <LI>B_regto_A.gif a gif image showing the results of the registration,
@@ -219,9 +224,9 @@ the images to the halfway positions.
 </UL>
 
 <!-- }}} -->
-<!-- {{{ Single-Time-Point Estimation -->
+<!-- {{{ SIENAX - Single-Time-Point Estimation -->
 
-<hr><H2>Single-Time-Point Estimation</H2>
+<a name="sienax"></a><p><hr><H2>SIENAX - Single-Time-Point Estimation</H2>
 
 <h3>Usage</h3>
 
@@ -230,9 +235,9 @@ href="sienax_usage">usage</a>) is run simply by typing
 
 <p><b>sienax &lt;input_fileroot&gt;</b>
 
-<p>where the input fileroot is an analyze image without the .hdr or
-.img extension. Note that the input fileroot must not contain
-directory names - i.e. all must be done within a single directory.
+<p>where the input fileroot is an image without any filename
+extension.  Note that the input fileroot must not contain directory
+names - i.e. all must be done within a single directory.
 
 
 <p>Other options are:
@@ -246,6 +251,8 @@ and vice versa
 <p><b>-2</b> : two-class segmentation (don't segment grey and white
 matter separately) - use this if there is poor grey/white contrast
 
+<p><b>-t2</b>: tell FAST that the input images are T2-weighted and not T1
+
 <p><b>-t &lt;t&gt;</b>: ignore from t (mm) upwards in Talairach space
 - if you need to ignore the top part of the head (e.g. if some
 subjects have the top missing and you need consistency across
@@ -253,6 +260,12 @@ subjects)
 
 <p><b>-b &lt;b&gt;</b>: ignore from b (mm) downwards in Talairach space; b should probably be -ve
 
+<p><b>-r</b>: tell FAST to estimate "regional" volumes as well as
+global; this produces peripheral cortex GM volume (3-class
+segmentation only) and ventricular CSF volume
+
+<p><b>-lm &lt;mask&gt;</b>: use a lesion (or lesion+CSF) mask to
+remove incorrectly labelled "grey matter" voxels
 
 
 <h3>What the script does</h3>
@@ -311,12 +324,40 @@ image is called "A"):
 
 <LI>A.sienax the output information from the <b>sienax</b> script.
 
-<LI>A_render.hdr a colour rendered image showing the segmentation
+<LI>A_render a colour rendered image showing the segmentation
 output superimposed on top of the original image.
 
 <LI>A2tal.mat the transformation that takes the input image into
 standard space.
 
+</UL>
+
+<!-- }}} -->
+<!-- {{{ Voxelwise SIENA Statistics -->
+
+<a name="sienar"></a><p><hr><H2>Voxelwise SIENA Statistics</H2>
+
+<p>We have recently extended SIENA to allow the voxelwise statistical
+analysis of atrophy across subjects. This takes a SIENA-derived edge
+flow image for each subject, warps these to align with a
+standard-space edge image and then carries out voxelwise cross-subject
+statistical analysis to identify brain edge points which, for example,
+are signficantly atrophic for the group of subjects as a whole, or
+where atrophy correlates significantly with age or disease
+progression.
+
+<p>In order to carry out voxelwise SIENA statistics, do the following:
+
+<UL>
+
+<LI> Run <b>siena &lt;A&gt: &lt;B&gt:</b> on all subjects.
+
+<LI> 
+
+
+
+
+
 </UL>
 
 <!-- }}} -->
@@ -383,7 +424,7 @@ standard space.
 <!-- }}} -->
 <!-- {{{ end -->
 
-<p><HR><FONT SIZE=1>Copyright &copy; 2000, University of
+<p><HR><FONT SIZE=1>Copyright &copy; 2000-2004, University of
 Oxford. Written by <A
 HREF="http://www.fmrib.ox.ac.uk/~steve/index.html">S. Smith</A>.</FONT>
 
-- 
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