Source code for nighres.intensity.mp2rageme_pd_mapping

import numpy as np
import nibabel as nb
import os
import sys
import nighresjava
from import load_volume, save_volume
from ..utils import _output_dir_4saving, _fname_4saving, \
                    _check_topology_lut_dir, _check_available_memory

[docs]def mp2rageme_pd_mapping(first_inversion, second_inversion, t1map, r2smap, echo_times, inversion_times, flip_angles, inversion_TR, excitation_TR, N_excitations, efficiency=0.96, b1map=None, save_data=False, overwrite=False, output_dir=None, file_name=None): """ MP2RAGEME PD mapping Estimate PD maps from MP2RAGEME data, combining T1 and R2* estimates with the MPRAGE model of [1]_ . Parameters ---------- first_inversion: [niimg] List of {magnitude, phase} images for the first inversion second_inversion: [niimg] List of {magnitude, phase} images for the second inversion t1map: niimg Quantitative T1 map image, in milliseconds r2smap: niimg Quantitative R2* map image, in kHz echo_times: [float] List of {te1, te2, te3, te4, te5} echo times, in seconds inversion_times: [float] List of {first, second} inversion times, in seconds flip_angles: [float] List of {first, second} flip angles, in degrees inversion_TR: float Inversion repetition time, in seconds excitation_TR: [float] List of {first,second} repetition times,in seconds N_excitations: int Number of excitations efficiency: float Inversion efficiency (default is 0.96) correct_B1: bool Whether to correct for B1 inhomogeneities (default is False) b1map: niimg Computed B1 map (optional) scale_phase: bool Whether to rescale the phase image in [0,2PI] or to assume it is already in radians save_data: bool Save output data to file (default is False) overwrite: bool Overwrite existing results (default is False) output_dir: str, optional Path to desired output directory, will be created if it doesn't exist file_name: str, optional Desired base name for output files with file extension (suffixes will be added) Returns ---------- dict Dictionary collecting outputs under the following keys (suffix of output files in brackets) * pd (niimg): Map of estimated proton density ratio (_qpd-map) Notes ---------- Original Java module by Pierre-Louis Bazin. References ---------- .. [1] Marques, Kober, Krueger, van der Zwaag, Van de Moortele, Gruetter (2010) MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field. doi: 10.1016/j.neuroimage.2009.10.002. """ print('\nPD Mapping') # make sure that saving related parameters are correct if save_data: output_dir = _output_dir_4saving(output_dir, first_inversion[0]) pd_file = os.path.join(output_dir, _fname_4saving(module=__name__,file_name=file_name, rootfile=first_inversion[0], suffix='qpd-map')) if overwrite is False \ and os.path.isfile(pd_file) : output = {'pd': pd_file} return output # start virtual machine, if not already running try: mem = _check_available_memory() nighresjava.initVM(initialheap=mem['init'], maxheap=mem['max']) except ValueError: pass # create algorithm instance qpdmap = nighresjava.IntensityMp2ragemePDmapping() # set algorithm parameters qpdmap.setFirstEchoTime(echo_times[0]) qpdmap.setFirstInversionTime(inversion_times[0]) qpdmap.setSecondInversionTime(inversion_times[1]) qpdmap.setFirstFlipAngle(flip_angles[0]) qpdmap.setSecondFlipAngle(flip_angles[1]) qpdmap.setInversionRepetitionTime(inversion_TR) qpdmap.setFirstExcitationRepetitionTime(excitation_TR[0]) qpdmap.setSecondExcitationRepetitionTime(excitation_TR[1]) qpdmap.setNumberExcitations(N_excitations) qpdmap.setInversionEfficiency(efficiency) qpdmap.setCorrectB1inhomogeneities(b1map!=None) # load first image and use it to set dimensions and resolution img = load_volume(first_inversion[0]) data = img.get_data() #data = data[0:10,0:10,0:10] affine = img.affine header = img.header resolution = [x.item() for x in header.get_zooms()] dimensions = data.shape qpdmap.setDimensions(dimensions[0], dimensions[1], dimensions[2]) qpdmap.setResolutions(resolution[0], resolution[1], resolution[2]) # input images qpdmap.setFirstInversionMagnitude(nighresjava.JArray('float')( (data.flatten('F')).astype(float))) data = load_volume(first_inversion[1]).get_data() qpdmap.setFirstInversionPhase(nighresjava.JArray('float')( (data.flatten('F')).astype(float))) data = load_volume(second_inversion[0]).get_data() qpdmap.setSecondInversionMagnitude(nighresjava.JArray('float')( (data.flatten('F')).astype(float))) data = load_volume(second_inversion[1]).get_data() qpdmap.setSecondInversionPhase(nighresjava.JArray('float')( (data.flatten('F')).astype(float))) data = load_volume(t1map).get_data() qpdmap.setT1mapImage(nighresjava.JArray('float')( (data.flatten('F')).astype(float))) data = load_volume(r2smap).get_data() qpdmap.setR2smapImage(nighresjava.JArray('float')( (data.flatten('F')).astype(float))) if (b1map!=None): data = load_volume(b1map).get_data() qpdmap.setB1mapImage(nighresjava.JArray('float')( (data.flatten('F')).astype(float))) # execute the algorithm try: qpdmap.execute() except: # if the Java module fails, reraise the error it throws print("\n The underlying Java code did not execute cleanly: ") print(sys.exc_info()[0]) raise return # reshape output to what nibabel likes pd_data = np.reshape(np.array(qpdmap.getProtonDensityImage(), dtype=np.float32), dimensions, 'F') # adapt header max for each image so that correct max is displayed # and create nifiti objects header['cal_min'] = np.nanmin(pd_data) header['cal_max'] = np.nanmax(pd_data) pd = nb.Nifti1Image(pd_data, affine, header) if save_data: save_volume(pd_file, pd) return {'pd': pd_file} else: return {'pd': pd}