How to use ismrmrd - 2 common examples

To help you get started, we’ve selected a few ismrmrd examples, based on popular ways it is used in public projects.

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github MRSRL / dl-cs / data_prep.py View on Github external
def ismrmrd_to_np(filename):
    """Read ISMRMRD data file to numpy array"""
    logger.debug('Loading file {}...'.format(filename))
    dataset = ismrmrd.Dataset(filename, create_if_needed=False)
    header = ismrmrd.xsd.CreateFromDocument(dataset.read_xml_header())
    num_kx = header.encoding[0].encodedSpace.matrixSize.x
    num_ky = header.encoding[0].encodingLimits.kspace_encoding_step_1.maximum
    num_slices = header.encoding[0].encodingLimits.slice.maximum + 1
    num_channels = header.acquisitionSystemInformation.receiverChannels

    try:
        rec_std = dataset.read_array('rec_std', 0)
        rec_weight = 1.0 / (rec_std**2)
        rec_weight = np.sqrt(rec_weight / np.sum(rec_weight))
        logger.debug('  Using rec std...')
    except Exception:
        rec_weight = np.ones(num_channels)
    opt_mat = np.diag(rec_weight)
    kspace = np.zeros([num_channels, num_slices, num_ky, num_kx],
                      dtype=np.complex64)
github MRSRL / dl-cs / data_prep.py View on Github external
def ismrmrd_to_np(filename):
    """Read ISMRMRD data file to numpy array"""
    logger.debug('Loading file {}...'.format(filename))
    dataset = ismrmrd.Dataset(filename, create_if_needed=False)
    header = ismrmrd.xsd.CreateFromDocument(dataset.read_xml_header())
    num_kx = header.encoding[0].encodedSpace.matrixSize.x
    num_ky = header.encoding[0].encodingLimits.kspace_encoding_step_1.maximum
    num_slices = header.encoding[0].encodingLimits.slice.maximum + 1
    num_channels = header.acquisitionSystemInformation.receiverChannels

    try:
        rec_std = dataset.read_array('rec_std', 0)
        rec_weight = 1.0 / (rec_std**2)
        rec_weight = np.sqrt(rec_weight / np.sum(rec_weight))
        logger.debug('  Using rec std...')
    except Exception:
        rec_weight = np.ones(num_channels)
    opt_mat = np.diag(rec_weight)
    kspace = np.zeros([num_channels, num_slices, num_ky, num_kx],
                      dtype=np.complex64)
    num_acq = dataset.number_of_acquisitions()

ismrmrd

Python implementation of the ISMRMRD

Public-Domain
Latest version published 12 months ago

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