def __init__(self, subject): GenericTask.__init__(self, subject)
def __init__(self, subject): GenericTask.__init__(self, subject, 'preparation', 'unwarping', 'denoising', 'preprocessing', 'parcellation', 'registration') self.reportName = self.config.get('qa','report_name') self.imgWidth = 650 self.debug = False
def __init__(self, subject): GenericTask.__init__(self, subject, 'preprocessing', 'preparation', 'unwarping', 'masking')
def __init__(self, subject): GenericTask.__init__(self, subject, 'preparation')
def __init__(self, subject): GenericTask.__init__(self, subject, 'hardi', 'masking')
def __init__(self, subject): GenericTask.__init__(self, subject, 'hardi', 'registration' ,'masking')
def __init__(self, subject): GenericTask.__init__(self, subject, 'tensors', 'masking')
def __init__(self, subject): GenericTask.__init__(self, subject, 'denoising', 'preparation', 'unwarping')
def __init__(self, subject): GenericTask.__init__(self, subject, 'preparation') self.id = subject.getConfig().get('parcellation', 'id')
def __init__(self, subject): """Fits a diffusion tensor model at each voxel """ GenericTask.__init__(self, subject, 'preprocessing', 'preparation', 'unwarping', 'masking')
def __init__(self, subject): GenericTask.__init__(self, subject, 'tensors', 'masking', 'unwarping', 'preprocessing', 'preparation', 'registration')
def __init__(self, subject): GenericTask.__init__(self, subject, "preparation", "parcellation")
def __init__(self, subject): GenericTask.__init__(self, subject, 'preprocessing', 'parcellation', 'preparation')
def __init__(self, subject): self.subjectDir = subject.getDir() GenericTask.__init__(self, subject) self.setCleanupBeforeImplement(False)
def __init__(self, subject): GenericTask.__init__(self, subject, 'registration')
def __init__(self, subject): GenericTask.__init__(self, subject, 'backup')