denoising:
adaptative denoising:
segmentation:
Pierrick Coupé, , José V. Manjón, Vladimir Fonov, Jens Pruessner, Montserrat Robles, D. Louis Collins "Patch-based segmentation using expert priors: Application to hippocampus and ventricle segmentation" http://dx.doi.org/10.1016/j.neuroimage.2010.09.018
"MICCAI 2012 Workshop on Multi-Atlas Labeling" ISBN-10: 1479126187 entry BIC-IPL and BIC-IPL-HR, https://masi.vuse.vanderbilt.edu/workshop2012/images/c/c8/MICCAI_2012_Workshop_v2.pdf
Katrin Weier, Vladimir Fonov, Karyne Lavoie, Julien Doyon and D. Louis Collins "Rapid automatic segmentation of the human cerebellum and its lobules (RASCAL) Implementation and application of the patch-based label-fusion technique with a template library to segment the human cerebellum" http://dx.doi.org/10.1002/hbm.22529
grading:
These programs were originally designed to be used with MINC files, but should work with any file format supported by ITK version 4 Most tools have an optional paramter called search radius - which specifies how non-local the search should be (in voxels) and patch radius - the radius of the local patch used to extract features.
Denoising requires specifying noise level ($sigma
), and optionall search radius $search_radius
and patch radius $patch_radius
itk_minc_nonlocal_filter input.mnc output.mnc --noise $sigma --search $search_radius --patch $patch_radius
Adaptative denoising have optional parameters: search radius $search_radius
and patch radius $patch_radius
itk_minc_nonlocal_filter input.mnc output.mnc --search $search_radius --patch $patch_radius --anlm
All segmentation tools and scripts require library of labelled samples.
Segmetnation tool require library of presegmented examples $train
, number of classes including background $classes
and optionally search radius and patch radius
Training examples are referenced in a comma separated file in the format: <image.mnc>,<labels.mnc>
itk_patch_morphology input.mnc output_labels.mnc --discrete $classes --search $search_radius --patch $patch_radius --train $train
Several high level scripts are included in scripts
directory:
ventricles_segmentation_pipeline.pl
- segmentation script for latera ventricle segmentation, uses volume_patches program from legacy directoryhcag_segmentation_pipeline.pl
- Hippocampus and Amygdala segmentation scriptmiccai2012_segmentation_minipipe.pl
- whole head segmentation pipeline, used in MICCAI 2012 Grand Challenge and Workshop on Multi-Atlas Labelingpatch_segmentation_pipeline.pl
- generic segmetnation script used in RASCAL paperAll grading tools and scripts require library of labelled samples.
Similar to segmetnation tool, grading require library of presegmented examples $train
and optionally search radius and patch radius
Training examples are referenced in a comma separated file in the format: <image.mnc>,<labels.mnc>,<grading>
Two training libraries can be provided , which are both loaded (and optionally each is used independently for pre-selection)
itk_patch_morphology input.mnc --grading output_grading.mnc --search $search_radius --patch $patch_radius --train $train --train2 $train2
High level script for simultaneous grading and segmentation: scripts/snipe_grading_pipeline.pl