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dipy_CNS2011.lyx
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dipy_CNS2011.lyx
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#LyX 1.6.7 created this file. For more info see http://www.lyx.org/
\lyxformat 345
\begin_document
\begin_header
\textclass article
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\language english
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\end_header
\begin_body
\begin_layout Title
Building an open platform for advanced diffusion MRI analysis
\end_layout
\begin_layout Standard
Diffusion-weighted MR imaging (dMRI) is a non-invasive technique which can
reveal important information about the directional organisation of the
white matter fibres of the brain.
Tractography is a way to approximate these neuronal pathways using streamlines
and connectivity profiles.
dMRI has been lately used not only to study the structure of the brain
but also of other organs such as heart, spine, and liver.
Deriving tractography from the raw MR data calls for a wide range of signal
processing, medical imaging and machine learning techniques.
These we have provided in the dipy toolbox.
\end_layout
\begin_layout Standard
Dipy[1] stands for diffusion imaging in python and is a free, open source,
python toolbox.
It provides a library of algorithms to give a full data processing pathway
from raw diffusion magnetic resonance data to tractographies, with several
novel algorithms for analysing, comparing and displaying tractographies.
Our algorithms are designed to allow very quick analyses of the huge datasets
that typically are involved in tractography.
Dipy operates across all standard platforms and inter-operates with the
file formats of a wide range of other brain imaging software.
\end_layout
\begin_layout Standard
Dipy was initially developed by researchers from the University of Cambridge
and the MRC Cognition and Brain Sciences Unit but now has many other internatio
nal contributors.
The aim of dipy is to make it easier to do better diffusion MR imaging
research.
This it achieves by clearly written, and clearly explained, code with a
good fit to the underlying concepts, designed in a way that fosters large
scale collaborative development using the latest software engineering principle
s.
\end_layout
\begin_layout Standard
We believe that by understanding the underlying anatomy in vivo and by providing
the tools to compare different populations we will be able to help researchers
and medical practitioners with new ways to investigate and understand the
structure of the complex neuronal pathways in the brain in health or disease.
\end_layout
\begin_layout Standard
[1] http://www.dipy.org
\begin_inset Newline newline
\end_inset
\begin_inset Newline newline
\end_inset
\end_layout
\begin_layout Standard
neuronal pathways
\end_layout
\begin_layout Standard
what diffusion is useful for
\end_layout
\begin_layout Standard
fibrous structures musle, heart, spine
\end_layout
\begin_layout Standard
What our analysis does?
\end_layout
\begin_layout Standard
* Reconstruction algorithms, e.g.
GQI, DTI
\end_layout
\begin_layout Standard
* Tractography generation algorithms, e.g.
EuDX
\end_layout
\begin_layout Standard
* Intelligent downsampling of tracks
\end_layout
\begin_layout Standard
* Ultra fast tractography clustering
\end_layout
\begin_layout Standard
* Resampling datasets with anisotropic voxels to isotropic
\end_layout
\begin_layout Standard
* Visualizing multiple brains simultaneously
\end_layout
\begin_layout Standard
* Finding track correspondence between different brains
\end_layout
\begin_layout Standard
* Warping tractographies into another space, e.g.
MNI space
\end_layout
\begin_layout Standard
* Reading many different file formats, e.g.
Trackvis or NIfTI
\end_layout
\begin_layout Standard
* Dealing with huge tractographies without memory restrictions
\end_layout
\begin_layout Standard
* Playing with datasets interactively without storing
\begin_inset Newline newline
\end_inset
\begin_inset Newline newline
\end_inset
\begin_inset Newline newline
\end_inset
\end_layout
\begin_layout Standard
Why is it important?
\end_layout
\begin_layout Itemize
A new way to investigate the structure of the neuronal pathways in the brain
\end_layout
\begin_layout Itemize
It gives you an environment that you can clarify your thinking about problems
of tractography and their solutions interacting with visualizations
\end_layout
\begin_layout Itemize
Better software engineering principles - free, open, fast, easy to understand
to understand the underlying principles & use and explore the similarities
and divergencies between different approaches.
\end_layout
\begin_layout Itemize
Python is a human friendly language with no licencing issues.
\end_layout
\begin_layout Itemize
New algorithms - simplifying complex datasets
\end_layout
\begin_layout Itemize
Well documented with good examples
\end_layout
\begin_layout Standard
How do we feel about this breakthrough?
\end_layout
\end_body
\end_document