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Merge pull request #1155 from nipreps/fix/multi-echo-bold
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ENH: Large overhaul of the functional workflow w/focus on ME-EPI
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@oesteban
oesteban authored Nov 19, 2023
2 parents 2de61ac + d4956ff commit 3752c5d
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Showing 17 changed files with 598 additions and 311 deletions.
2 changes: 1 addition & 1 deletion docs/source/conf.py
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Expand Up @@ -90,7 +90,7 @@
#
# This is also used if you do content translation via gettext catalogs.
# Usually you set "language" from the command line for these cases.
language = None
language = "en"

# There are two options for replacing |today|: either, you set today to some
# non-false value, then it is used:
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17 changes: 10 additions & 7 deletions mriqc/cli/parser.py
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Expand Up @@ -538,7 +538,7 @@ def parse_args(args=None, namespace=None):
config.execution.participant_label,
session_id=config.execution.session_id,
task=config.execution.task_id,
group_echos=False,
group_echos=True,
bids_filters=config.execution.bids_filters,
queries={mod: DEFAULT_BIDS_QUERIES[mod] for mod in lc_modalities}
)
Expand Down Expand Up @@ -575,7 +575,7 @@ def parse_args(args=None, namespace=None):
# Estimate the biggest file size / leave 1GB if some file does not exist (datalad)
with suppress(FileNotFoundError):
config.workflow.biggest_file_gb = _get_biggest_file_size_gb(
[i for sublist in config.workflow.inputs.values() for i in sublist]
config.workflow.inputs.values()
)

# set specifics for alternative populations
Expand All @@ -593,11 +593,14 @@ def parse_args(args=None, namespace=None):


def _get_biggest_file_size_gb(files):
"""Identify the largest file size (allows multi-echo groups)."""

import os

max_size = 0
sizes = []
for file in files:
size = os.path.getsize(file) / (1024**3)
if size > max_size:
max_size = size
return max_size
if isinstance(file, (list, tuple)):
sizes.append(_get_biggest_file_size_gb(file))
else:
sizes.append(os.path.getsize(file))
return max(sizes) / (1024**3)
59 changes: 20 additions & 39 deletions mriqc/data/bootstrap-func.yml
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Expand Up @@ -26,69 +26,50 @@
###########################################################################

packagename: mriqc
title: '{filename} :: Functional MRIQC report'
title: "{filename} :: MRIQC's BOLD fMRI report"
sections:
- name: Summary
reportlets:
- bids: {datatype: figures, desc: summary, extension: [.html]}
- name: Basic visual report
- name: Basic echo-wise reports
ordering: echo
reportlets:
- bids: {datatype: figures, desc: zoomed}
caption: This panel shows a mosaic of the brain. This mosaic is the most suitable to
screen head-motion intensity inhomogeneities, global/local noise, signal leakage
(for example, from the eyeballs and across the phase-encoding axis), etc.
subtitle: Voxel-wise average of BOLD time-series, zoomed-in covering just the brain
- bids: {datatype: figures, desc: stdev}
subtitle: Standard deviation of signal through time
caption: The voxel-wise standard deviation of the signal (variability along time).
- bids: {datatype: figures, desc: carpet}
subtitle: Carpetplot and nuisance signals
caption: The so-called «carpetplot» may assist in assessing head-motion
derived artifacts and respiation effects.
- name: Extended visual report
- name: Extended reports shared across echos
reportlets:
- bids: {datatype: figures, desc: background}
caption: This panel shows a mosaic enhancing the background around the head.
Artifacts usually unveil themselves in the air surrounding the head, where no signal
sources are present.
subtitle: View of the background of the voxel-wise average of the BOLD timeseries
- bids: {datatype: figures, desc: mean}
subtitle: Average signal through time
caption: The average signal calculated across the last axis (time).
- bids: {datatype: figures, desc: airmask}
caption: The <em>hat</em>-mask calculated internally by MRIQC. Some metrics will use this
mask, for instance, to find out artifacts and estimate the spread of gaussian noise
added to the signal. This mask leaves out the air around the face to avoid measuring
noise sourcing from the eyeballs and their movement.
subtitle: '&laquo;Hat&raquo;-mask'
- bids: {datatype: figures, desc: noisefit}
caption: The noise fit internally estimated by MRIQC to calculate the QI<sub>1</sub> index
proposed by <a href="https://doi.org/10.1002/mrm.21992" target="_blank">Mortamet et al. (2009)</a>.
subtitle: Distribution of the noise within the <em>hat</em> mask
style:
max-width: 450px
- bids: {datatype: figures, desc: artifacts}
caption: Mask of artifactual intensities identified within the <em>hat</em>-mask.
subtitle: Artifactual intensities on the background
- bids: {datatype: figures, desc: brainmask}
caption: Brain mask as internally extracted by MRIQC. Defects on the brainmask could
indicate problematic aspects of the image quality-wise.
subtitle: Brain extraction performance
- bids: {datatype: figures, desc: head}
caption: A mask of the head calculated internally by MRIQC.
subtitle: Head mask
- bids: {datatype: figures, desc: segmentation}
caption: Brain tissue segmentation, as internally extracted by MRIQC.
Defects on this segmentation, as well as noisy tissue labels could
indicate problematic aspects of the image quality-wise.
subtitle: Brain tissue segmentation
- bids: {datatype: figures, desc: norm}
caption: This panel shows a <em>quick-and-dirty</em> nonlinear registration into
the <code>MNI152NLin2009cAsym</code> template accessed with
<a href="https://templateflow.org/browse" target="_blank"><em>TemplateFlow</em></a>.
subtitle: Spatial normalization of the anatomical image
static: false

- name: Extended echo-wise reports
ordering: echo
reportlets:
- bids: {datatype: figures, desc: background}
caption: This panel shows a mosaic enhancing the background around the head.
Artifacts usually unveil themselves in the air surrounding the head, where no signal
sources are present.
subtitle: View of the background of the voxel-wise average of the BOLD timeseries
- bids: {datatype: figures, desc: mean}
subtitle: Average signal through time
caption: The average signal calculated across the last axis (time).
- bids: {datatype: figures, desc: zoomed}
caption: This panel shows a mosaic of the brain. This mosaic is the most suitable to
screen head-motion intensity inhomogeneities, global/local noise, signal leakage
(for example, from the eyeballs and across the phase-encoding axis), etc.
subtitle: Voxel-wise average of BOLD time-series, zoomed-in covering just the brain

- name: About
nested: true
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18 changes: 9 additions & 9 deletions mriqc/data/testdata/group_bold.tsv
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bids_name aor aqi dummy_trs dvars_nstd dvars_std dvars_vstd efc fber fd_mean fd_num fd_perc fwhm_avg fwhm_x fwhm_y fwhm_z gcor gsr_x gsr_y size_t size_x size_y size_z snr spacing_tr spacing_x spacing_y spacing_z summary_bg_k summary_bg_mad summary_bg_mean summary_bg_median summary_bg_n summary_bg_p05 summary_bg_p95 summary_bg_stdv summary_fg_k summary_fg_mad summary_fg_mean summary_fg_median summary_fg_n summary_fg_p05 summary_fg_p95 summary_fg_stdv tsnr
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sub-ds205s07_task-view_run-01_bold 0.0037941304347826085 0.009004425434782607 0 21.771277794505497 1.0383257392307694 0.9654323329670328 0.5374363883770776 996.05810546875 0.1520993052375479 15 16.304347826086957 1.8006975 1.698995 1.8907725 1.812325 0.0408048 -0.005473143886774778 0.029460299760103226 92 53 53 27 5.072217446804501 2.200000047683716 4.0 4.0 4.0 27.23682449098333 6.229042844827164 39.84597218066951 22.68582057952881 56266.0 13.13893985748291 139.88406372070312 53.19358553170623 0.3440927682297894 134.06510192792 720.2195639126317 715.9733276367188 19577.0 476.44183349609375 949.2680053710938 141.1522768548468 57.291603088378906
sub-ds205s07_task-view_run-02_bold 0.001657826086956522 0.008996689347826086 0 21.519903371868143 1.03221585 0.9588135309890113 0.5394046827226318 978.5082397460938 0.15451170465747024 18 19.565217391304348 1.8057741666666667 1.7069875 1.8966275 1.8137075 0.0433865 -0.006386041175574064 0.03140100836753845 92 53 53 27 5.056518385567245 2.200000047683716 4.0 4.0 4.0 29.670872739050793 6.462488049835068 40.8786782498388 22.991168975830078 56204.0 13.375846862792969 145.70977783203125 55.307788548732276 0.4335730121828525 135.24980824168193 723.5399965684157 719.189453125 19639.0 481.1661376953125 953.2984008789062 142.22654558293314 59.76730728149414
sub-ds205s09_task-view_acq-LR_run-01_bold 0.002976986301369863 0.013025251780821916 0 21.405761824861116 1.0611945656944441 0.9949810694444441 0.513063203363028 1207.71533203125 0.3258302280827085 45 61.64383561643836 1.7912675 1.6990475 1.91971 1.755045 0.0362147 -0.005499124526977539 0.01900400035083294 73 53 53 27 5.854353348400624 2.200000047683716 4.0 4.0 4.0 25.199608221336092 5.712747254148226 39.895556611046395 23.25909996032715 58097.0 15.119007110595703 139.44947814941406 56.095377999258176 1.178096485114681 117.15050549333893 796.3205729290771 808.3048706054688 17746.0 526.5880737304688 995.4718627929688 138.0651368134319 58.34690284729004
sub-ds205s09_task-view_acq-LR_run-02_bold 0.005996575342465754 0.015215327260273973 0 34.39419094722222 1.6192232063888892 1.6501877419444442 0.5136460861041277 1192.3255615234375 0.3345943377548133 47 64.38356164383562 1.7920308333333335 1.6996125 1.920615 1.755865 0.0313875 -0.005142268259078264 0.018914325162768364 73 53 53 27 5.851459215059082 2.200000047683716 4.0 4.0 4.0 25.07199243533304 5.957362424448292 40.199861866481136 23.448966026306152 58096.0 15.263423919677734 139.87855529785156 56.15791257667716 1.1742077271466247 117.28293886411426 797.5247600734042 809.6943969726562 17747.0 526.8685302734375 997.0792846679688 138.3708840384822 51.352577209472656
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sub-ds205s03_task-view_run-01_bold 0.004324782608695651 0.008262664456521738 0 21.120018382857136 1.0831709981318685 1.0370256236263742 0.5459090166346154 1002.2031860351562 0.16520736608810047 18 19.565217391304348 2.342805 2.234215 2.613075 2.181125 0.0235103 -0.0050179013051092625 0.04793250188231468 92 53 53 27 4.4829699247170405 2.200000047683716 4.0 4.0 4.0 29.71988008857921 7.139052847581331 46.66574967004908 24.7608699798584 55362.0 0.032608695328235626 164.9891357421875 71.66784333938988 1.596677545134333 133.64368600192023 779.8773281882851 783.8695678710938 20481.0 457.5434875488281 1054.61962890625 174.85070038268285 62.58223795099184
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sub-ds205s09_task-view_acq-LR_run-01_bold 0.003159041095890411 0.010028379999999998 0 20.396152721388898 1.090989740416667 1.0059027894444443 0.5048353890125871 1243.320556640625 0.3258302280827085 45 61.64383561643836 2.0852608333333333 2.0588275 2.2995125 1.8974425 0.0461463 -0.0019858605228364468 0.021903924643993378 73 53 53 27 5.292682271102816 2.200000047683716 4.0 4.0 4.0 33.98009379704732 5.949264906571304 39.07313696894552 22.956466674804688 58369.0 1.0936830043792725 132.37034606933594 62.99641049623399 2.7398312528413937 115.58686871143783 791.6591133225957 809.4622802734375 17474.0 483.6707458496094 994.6715698242188 152.93552051211557 66.51667785644531
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3 changes: 3 additions & 0 deletions mriqc/data/tests/ds000005/sub-01/func/sub-01_task-mixedgamblestask_run-01_bold.json
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{
"EchoTime": 0.030
}
1 change: 1 addition & 0 deletions mriqc/data/tests/ds000005/sub-01/func/sub-01_task-mixedgamblestask_run-02_bold.json
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sub-01_task-mixedgamblestask_run-01_bold.json
1 change: 1 addition & 0 deletions mriqc/data/tests/ds000005/sub-01/func/sub-01_task-mixedgamblestask_run-03_bold.json
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sub-01_task-mixedgamblestask_run-01_bold.json
12 changes: 12 additions & 0 deletions mriqc/interfaces/bids.py
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Expand Up @@ -49,6 +49,7 @@ class IQMFileSinkInputSpec(DynamicTraitedSpec, BaseInterfaceInputSpec):
rec_id = traits.Either(None, Str, usedefault=True)
run_id = traits.Either(None, traits.Int, usedefault=True)
dataset = Str(desc="dataset identifier")
dismiss_entities = traits.List(["part"], usedefault=True)
metadata = traits.Dict()
provenance = traits.Dict()

Expand Down Expand Up @@ -111,6 +112,17 @@ def _gen_outfile(self):
break
in_file = str(path.relative_to(bids_root))

if (
isdefined(self.inputs.dismiss_entities)
and (dismiss := self.inputs.dismiss_entities)
):
for entity in dismiss:
bids_chunks = [
chunk for chunk in path.name.split("_")
if not chunk.startswith(f"{entity}-")
]
path = path.parent / "_".join(bids_chunks)

# Build path and ensure directory exists
bids_path = out_dir / in_file.replace("".join(Path(in_file).suffixes), ".json")
bids_path.parent.mkdir(parents=True, exist_ok=True)
Expand Down
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