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156 | 156 |
|
157 | 157 | % \hrule
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158 | 158 | \end{center}
|
159 |
| -\vspace{-1em} |
| 159 | +\vspace{0em} |
160 | 160 |
|
161 | 161 | %___________________________________________________________________________
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162 | 162 |
|
|
184 | 184 | \item Automated monitor calibration (supported photometers)
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185 | 185 | \end{itemize}
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186 | 186 | \includegraphics[width=\columnwidth]{../pics/psychopyBuilder.png}
|
187 |
| - |
| 187 | +\vspace{-2em} |
188 | 188 |
|
189 | 189 | %___________________________________________________________________________
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190 | 190 |
|
|
248 | 248 | \end{itemize}
|
249 | 249 | \includegraphics[width=\columnwidth]{../pics/nipy_viz.pdf}
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250 | 250 |
|
251 |
| - |
252 | 251 | %___________________________________________________________________________
|
253 | 252 |
|
254 | 253 | \ndproject{Nipype}{http://nipy.org/nipype}{blank.png}{.2}{-1.25em}{0em}
|
|
257 | 256 | of algorithms from different packages (e.g., SPM, FSL, FreeSurfer,
|
258 | 257 | Camino, AFNI, Slicer), eases the design of workflows within and
|
259 | 258 | between packages, and reduces the learning curve necessary to use
|
260 |
| -different packages. Nipype is creating a collaborative platform for |
261 |
| -neuroimaging software development in a high-level language and |
262 |
| -addressing limitations of existing pipeline systems. Nipype allows you to |
| 259 | +different packages. |
| 260 | +% Nipype is creating a collaborative platform for |
| 261 | +%neuroimaging software development in a high-level language and |
| 262 | +%addressing limitations of existing pipeline systems. |
| 263 | +Nipype allows you to |
263 | 264 | \begin{itemize}[nolistsep,topsep=0em,leftmargin=1pc]
|
264 |
| -\item easily interact with tools from different software packages |
265 |
| -\item combine processing steps from different software packages |
| 265 | +\item interact with tools from different software packages |
| 266 | +\item combine processing steps from different packages |
266 | 267 | \item develop new workflows faster by reusing common steps from old ones
|
267 |
| -\item process data faster by running it in parallel on many cores/machines |
| 268 | +\item process data faster by running in parallel% on many cores/machines |
268 | 269 | \item make your research easily reproducible
|
269 | 270 | \item share your processing workflows with the community
|
270 | 271 | \end{itemize}
|
| 272 | +\vspace{-1em} |
271 | 273 | \includegraphics[width=\columnwidth]{nipype_arch.pdf}
|
272 |
| -\ndcite{Gorgolewski K, Burns CD, Madison C, Clark D, Halchenko YO, Waskom ML, Ghosh SS |
273 |
| -(2011) Nipype: a flexible, lightweight and extensible neuroimaging data |
274 |
| -processing framework in Python. Front. Neuroinform. 5:13. |
275 |
| -doi: 10.3389/fninf.2011.00013} |
| 274 | +\vspace{-3em} |
| 275 | + |
| 276 | +\ndcite{Gorgolewski K, Burns CD, Madison C, Clark D, |
| 277 | + Halchenko YO, Waskom ML, Ghosh SS (2011) Nipype: a flexible, |
| 278 | + lightweight and extensible neuroimaging data processing framework in |
| 279 | + Python. Front. Neuroinform. 5:13. doi: 10.3389/fninf.2011.00013} |
276 | 280 |
|
277 | 281 |
|
278 | 282 | %___________________________________________________________________________
|
|
337 | 341 | \includegraphics[width=\columnwidth]{pymvpa_shot.pdf}
|
338 | 342 | \ndcite{Hanke, M., Halchenko, Y. O., Sederberg, P. B., Hanson,
|
339 | 343 | S. J., Haxby, J. V. \& Pollmann, S. (2009).
|
340 |
| - PyMVPA: A Python toolbox for multivariate pattern analysis of fMRI data. Neuroinformatics, 7}\\ |
341 |
| -\ndcite{Haxby, J. V. , Guntupalli, J. S. , Connolly, A. C. , |
342 |
| - Halchenko, Y. O. , Conroy, B. R., Gobbini, M. I. , Hanke, M. and |
343 |
| - Ramadge, P. J. (2011). A Common, High-Dimensional Model of the |
344 |
| - Representational Space in Human Ventral Temporal Cortex. Neuron, |
345 |
| - 72.} |
| 344 | + PyMVPA: A Python toolbox for multivariate pattern analysis of fMRI data. Neuroinformatics}\\ |
| 345 | +%\ndcite{Haxby, J. V. , Guntupalli, J. S. , Connolly, A. C. , |
| 346 | +% Halchenko, Y. O. , Conroy, B. R., Gobbini, M. I. , Hanke, M. and |
| 347 | +% Ramadge, P. J. (2011). A Common, High-Dimensional Model of the |
| 348 | +% Representational Space in Human Ventral Temporal Cortex. Neuron, |
| 349 | +% 72.} |
346 | 350 |
|
347 | 351 | %___________________________________________________________________________
|
348 | 352 |
|
|
353 | 357 | helping researchers in developing new neuroimaging tools, sharing data and
|
354 | 358 | distributing their software.
|
355 | 359 | \begin{itemize}[nolistsep,topsep=0em,leftmargin=1pc]
|
356 |
| -\item Written in pure Python |
| 360 | +%\item Written in pure Python |
357 | 361 | \item Databasing capabilities
|
358 | 362 | \item Massive computation facilities using Soma-workflow
|
359 | 363 | \item Open environment, with many toolboxes
|
|
370 | 374 |
|
371 | 375 | %___________________________________________________________________________
|
372 | 376 |
|
373 |
| -\ndproject{AIMS}{http://brainvisa.info}{blank.png}{.2}{-1.25em}{0em} |
374 |
| - |
375 |
| -AIMS is the image processing library provided within the BrainVISA environment. |
376 |
| -It is independent from BrainVISA, and the basis for the Anatomist viewer. |
377 |
| -\begin{itemize}[nolistsep,topsep=0em,leftmargin=1pc] |
378 |
| -\item C++ and Python APIs, including integration with Numpy arrays |
379 |
| -\item Open and plugin-based IO system supporting various volume formats (NIFTI-1, |
380 |
| -Analyze, DICOM, MINC, ECAT, and several others including all standard 2D |
381 |
| -image formats), several mesh and texture formats (GIFTI, PLY, |
382 |
| -% CIVET, BrainVisa Mesh and Tri, export as VRML-1, POV, |
383 |
| -\ldots), graphs. |
384 |
| -\item Many neuromiaging data manipulation tools and image processing algorithms |
385 |
| -\end{itemize} |
| 377 | +% \ndproject{AIMS}{http://brainvisa.info}{blank.png}{.2}{-2.25em}{0em} |
| 378 | +% |
| 379 | +% AIMS is the image processing library provided within the BrainVISA environment. |
| 380 | +% It is independent from BrainVISA, and the basis for the Anatomist viewer. |
| 381 | +% \begin{itemize}[nolistsep,topsep=0em,leftmargin=1pc] |
| 382 | +% \item C++ and Python APIs, including integration with Numpy arrays |
| 383 | +% \item Open and plugin-based IO system supporting various volume formats (NIFTI-1, |
| 384 | +% Analyze, DICOM, MINC, ECAT, and several others including all standard 2D |
| 385 | +% image formats), several mesh and texture formats (GIFTI, PLY, |
| 386 | +% % CIVET, BrainVisa Mesh and Tri, export as VRML-1, POV, |
| 387 | +% \ldots), graphs. |
| 388 | +% \item Many neuromiaging data manipulation tools and image processing algorithms |
| 389 | +% \end{itemize} |
386 | 390 |
|
387 | 391 | %___________________________________________________________________________
|
388 | 392 |
|
|
431 | 435 | independent part of the BrainVisa environment, and relies on the AIMS
|
432 | 436 | library, inheriting its features.
|
433 | 437 | \begin{itemize}[nolistsep,topsep=0em,leftmargin=1pc]
|
434 |
| -\item C++ and Python APIs |
| 438 | +% \item C++ and Python APIs |
435 | 439 | \item Interactive, fast 3D via direct OpenGL
|
436 |
| -\item Usable as a standalone software or as a library to build dedicated GUIs |
| 440 | +\item Usable as a standalone software or as a library% to build dedicated GUIs |
437 | 441 | \item Supports all kinds of neuroimaging objects, including complex structured
|
438 | 442 | objects
|
439 | 443 | \item Interactive ROI drawing, voxel-based or on surfaces
|
|
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