AFQ.recognition.criteria

Module Contents

Functions

prob_map(b_sls, bundle_def, preproc_imap, ...)
cross_midline(b_sls, bundle_def, preproc_imap, **kwargs)
start(b_sls, bundle_def, preproc_imap, **kwargs)
end(b_sls, bundle_def, preproc_imap, **kwargs)
length(b_sls, bundle_def, preproc_imap, **kwargs)
primary_axis(b_sls, bundle_def, **kwargs)
include(b_sls, bundle_def, preproc_imap, max_includes, ...)
curvature(b_sls, bundle_def, mapping, img, ...)	Filters streamlines by how well they match
exclude(b_sls, bundle_def, preproc_imap, **kwargs)
recobundles(b_sls, mapping, bundle_def, reg_template, ...)
qb_thresh(b_sls, bundle_def, preproc_imap, clip_edges, ...)
mahalanobis(b_sls, bundle_def, clip_edges, ...)
run_bundle_rec_plan(bundle_dict, tg, mapping, img, ...)

Attributes

bundle_criterion_order
logger

AFQ.recognition.criteria.bundle_criterion_order = ['prob_map', 'cross_midline', 'start', 'end', 'length', 'primary_axis', 'include', 'exclude',...

AFQ.recognition.criteria.logger

AFQ.recognition.criteria.prob_map(b_sls, bundle_def, preproc_imap, prob_threshold, **kwargs)

AFQ.recognition.criteria.cross_midline(b_sls, bundle_def, preproc_imap, **kwargs)

AFQ.recognition.criteria.start(b_sls, bundle_def, preproc_imap, **kwargs)

AFQ.recognition.criteria.end(b_sls, bundle_def, preproc_imap, **kwargs)

AFQ.recognition.criteria.length(b_sls, bundle_def, preproc_imap, **kwargs)

AFQ.recognition.criteria.primary_axis(b_sls, bundle_def, **kwargs)

AFQ.recognition.criteria.include(b_sls, bundle_def, preproc_imap, max_includes, parallel_segmentation, **kwargs)

AFQ.recognition.criteria.curvature(b_sls, bundle_def, mapping, img, save_intermediates, **kwargs)

Filters streamlines by how well they match a curve in orientation and shape but not scale

AFQ.recognition.criteria.exclude(b_sls, bundle_def, preproc_imap, **kwargs)

AFQ.recognition.criteria.recobundles(b_sls, mapping, bundle_def, reg_template, img, refine_reco, save_intermediates, rng, rb_recognize_params, **kwargs)

AFQ.recognition.criteria.qb_thresh(b_sls, bundle_def, preproc_imap, clip_edges, **kwargs)

AFQ.recognition.criteria.mahalanobis(b_sls, bundle_def, clip_edges, cleaning_params, **kwargs)

AFQ.recognition.criteria.run_bundle_rec_plan(bundle_dict, tg, mapping, img, reg_template, preproc_imap, bundle_name, bundle_idx, bundle_to_flip, bundle_roi_dists, bundle_decisions, **segmentation_params)