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PySPIM Core Package

Core library for processing dual-view SPIM (diSPIM) microscopy data.

Overview

PySPIM provides the fundamental functionality for SPIM data analysis with GPU acceleration support.

Key Components

  • Data Loading - ΞΌManager acquisitions, TIFF, HDF5, Zarr
  • ROI Detection - Automated and manual region detection
  • Deskewing - Light sheet artifact correction
  • Registration - Multi-view alignment with GPU acceleration
  • Deconvolution - Richardson-Lucy with PSF support

Basic Usage

import pyspim
from pyspim.data import dispim as data
from pyspim import roi, deskew as dsk

# Load data
with data.uManagerAcquisition(data_path, False, numpy) as acq:
    a_raw = acq.get('a', 0, 0)
    b_raw = acq.get('b', 0, 0)

# ROI detection
roia = roi.detect_roi_3d(a_raw, 'otsu')
roib = roi.detect_roi_3d(b_raw, 'otsu')

# Deskewing
a_dsk = dsk.deskew_stage_scan(a_raw, pixel_size, step_size, 1)
b_dsk = dsk.deskew_stage_scan(b_raw, pixel_size, step_size, -1)

Performance Features

  • GPU Acceleration - CuPy integration for CUDA operations
  • Memory Efficient - Chunked processing for large datasets
  • Modular Design - Separate components for each processing step

Dependencies

  • Core: numpy, scikit-image
  • GPU: cupy (optional)
  • I/O: tifffile, h5py

Next Steps