Datasets:
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257c439 16fe2dd 257c439 16fe2dd 257c439 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 | """Reconstruct: beamform one rotation frame of the eSAF rotational 3D US dataset.
Loads a zea .hdf5 acquisition (raw RF channel data, one normal plane-wave
transmit per rotation frame), reads the acquisition parameters, and runs the
delay-and-sum beamforming pipeline configured in pipeline.yaml. The resulting
B-mode image is saved as a PNG, together with a plot of the per-frame probe
rotation angle (this dataset's special data: the linear array rotates 180
degrees about its axial axis, 1 degree per frame) so downstream users know how
to interpret the frame axis.
Usage:
python reconstruct.py
python reconstruct.py --input data/baseline_R45_H8__point_z080_r4.hdf5
python reconstruct.py --frame-index 45
"""
import os
# Default to the jax backend so the script runs without exporting KERAS_BACKEND.
os.environ.setdefault("KERAS_BACKEND", "jax")
os.environ.setdefault("MPLBACKEND", "Agg")
import argparse
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
import zea
from zea import Config, File, Pipeline
HERE = Path(__file__).parent
DEFAULT_INPUT = HERE / "data" / "baseline_R45_H8__point_z080_r4.hdf5"
DEFAULT_OUTPUT = HERE / "outputs" / "reconstruct_example.png"
CONFIG = HERE / "pipeline.yaml"
def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--input", type=Path, default=DEFAULT_INPUT)
parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT)
parser.add_argument(
"--frame-index",
type=int,
default=None,
help="rotation frame to beamform (default: frame closest to 90 deg, "
"where an off-axis target lies in the imaging plane)",
)
args = parser.parse_args()
if not args.input.exists():
raise FileNotFoundError(f"{args.input} not found.")
zea.init_device()
# Load the whole processing chain + parameters from pipeline.yaml
config = Config.from_path(str(CONFIG))
# Load file: acquisition parameters (with config overrides), one raw RF frame,
# and this dataset's special data — the probe rotation angle per frame.
with File(str(args.input)) as f:
parameters = f.load_parameters(**config.parameters)
rotation_angles_deg = np.asarray(
{c.name: c for c in f.custom}["rotation_angles_deg"].data
).ravel()
n_frames = f.data.raw_data.shape[0]
frame = args.frame_index
if frame is None: # default: frame where the probe has rotated ~90 deg
frame = int(np.argmin(np.abs(rotation_angles_deg - 90.0)))
raw = f.data.raw_data[frame : frame + 1] # (1, n_tx, n_ax, n_el, 1) — RF
print(f"raw_data frame : {raw.shape} ({n_frames} frames in file)")
# Build and run the beamforming pipeline defined in pipeline.yaml
pipeline = Pipeline.from_config(config)
inputs = pipeline.prepare_parameters(parameters)
outputs = pipeline(data=raw, **inputs)
recon = np.array(outputs["data"]) # (1, grid_z, grid_x), log-compressed dB
image = zea.display.to_8bit(
recon[0], dynamic_range=parameters.dynamic_range, pillow=False
)
# B-mode + rotation-angle plot (how to interpret the frame axis)
zea.visualize.set_mpl_style()
fig, axes = plt.subplots(
1, 2, figsize=(11, 5), gridspec_kw={"width_ratios": [1, 1.3]}
)
mm = plt.FuncFormatter(lambda v, _: f"{v * 1e3:.0f}")
axes[0].imshow(image, extent=parameters.extent_imshow, cmap="gray", aspect="equal")
axes[0].xaxis.set_major_formatter(mm)
axes[0].yaxis.set_major_formatter(mm)
axes[0].set(
title=f"B-mode frame {frame} @ {rotation_angles_deg[frame]:.0f} deg",
xlabel="Lateral [mm]",
ylabel="Depth [mm]",
)
axes[1].plot(np.arange(n_frames), rotation_angles_deg, color="tab:blue")
axes[1].axvline(frame, color="tab:red", linewidth=1.2, label="beamformed frame")
axes[1].set(
title="Probe rotation angle per frame\n(array rotates about its axial axis)",
xlabel="Frame index",
ylabel="Rotation angle [deg]",
)
axes[1].grid(True, color="0.85", linewidth=0.8)
axes[1].legend(loc="upper left", fontsize=8, frameon=False)
fig.suptitle(f"OpenH-RF eSAF rotational 3D US — {args.input.name}", y=0.98)
plt.tight_layout()
args.output.parent.mkdir(parents=True, exist_ok=True)
plt.savefig(str(args.output), bbox_inches="tight", dpi=150)
print(f"Reconstructed : {recon.shape}")
print(f"Saved : {args.output}")
if __name__ == "__main__":
main()
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