Roadmap¶

Alpha release checklist for ConfUSIus.

✅ Data I/O¶

• io module: load and save fUSI data in common formats.
  • AUTC beamformed IQ.
  • EchoFrame beamformed IQ.
  • NIfTI.
  • Zarr.
  • Iconeus SCAN (HDF5; see https://github.com/XunMa1214/fUS-toolbox).

✅ IQ Processing¶

• iq module: convert raw beamformed IQ data into functional images.
  • process_iq_blocks: apply a processing pipeline over sliding windows of IQ frames.
  • process_iq_to_power_doppler: compute power Doppler volumes from IQ blocks.
  • process_iq_to_axial_velocity: estimate axial blood velocity from IQ blocks.

✅ Signal Extraction¶

• extract module: extract voxel time series from spatial imaging data.
  • with_mask: flatten spatial dimensions into a voxel array using a boolean mask.
  • with_labels: extract region-averaged signals using an integer label map.
  • unmask: reconstruct a full spatial volume from a flat voxel array.

✅ Signal Preprocessing¶

• signal module: denoise and preprocess voxel time series.
  • censor_samples / interpolate_samples: mark or interpolate corrupted samples (e.g. motion outliers).
  • regress_confounds: remove nuisance signals via least-squares regression.
  • filter_butterworth: apply a low-pass, high-pass, or band-pass Butterworth filter.
  • standardize: scale signals to unit variance or percent signal change.
  • detrend: remove linear or polynomial trends from time series.

✅ Visualization¶

• plotting module: visualize fUSI volumes and time series.
  • plot_napari: interactive 3D/4D viewer with physical-space scaling.
  • plot_carpet: carpet plot (voxel × time raster) for quality control.
  • plot_volume: display 2D slices of a volume using matplotlib.pyplot.pcolormesh.
  • plot_contours: overlay region contours on imaging slices.

✅ Registration¶

• registration module: align fUSI volumes to a reference or template.
  • register_volumewise: register each frame in a 4D series to a reference volume.
  • compute_framewise_displacement: quantify frame-to-frame motion as a scalar displacement.
  • register_volume: rigid/affine/deformable registration of a single 3D volume.
  • resample_volume: resample a volume to a target affine and shape.

✅ Atlas¶

• atlas module: fetch and resample standard brain atlases.
  • BrainGlobe Atlas API wrapper for loading brain parcellations, returned as Xarray Datasets.

✅ Functional Connectivity¶

• connectivity module: compute functional connectivity from preprocessed fUSI time series (pairwise correlations, network metrics).
  • SeedBasedMaps: compute voxelwise correlation maps for a given seed region.
  • ConnectivityMatrix: compute pairwise connectivity matrices between regions of interest.

🚧 General Linear Models¶

• glm module: general linear model for stimulus-evoked and task-based fUSI analysis.