dosma.scan_sequences.QDess
- class dosma.scan_sequences.QDess(volumes: Sequence[dosma.core.med_volume.MedicalVolume])[source]
qDESS MRI sequence.
Quantitative double echo in steady state (qDESS) is a high-resolution scan that consists of two echos (S1, S2) that has shown high efficacy for analytic \(T_2\) mapping. Because of its high resolution, qDESS has been shown to be a good candidate for automatic segmentation.
DOSMA supports both automatic segmentation and analytical T2 solving for qDESS scans. Automated segmentation uses pre-trained convolutional neural networks (CNNs).
References
B Sveinsson, AS Chaudhari, GE Gold, BA Hargreaves. A simple analytic method for estimating \(T_2\) in the knee from DESS. Magnetic Resonance in Medicine, 38:63-70 (2017). [link]
- __init__(volumes: Sequence[dosma.core.med_volume.MedicalVolume])[source]
Methods
__init__(volumes)calc_rss()Calculate root-sum-of-squares (RSS) of two echos.
cmd_line_actions()Provide command line information (such as name, help strings, etc) as list of dictionary.
from_dicom(dir_or_files[, group_by, ...])Load scan from dicom files.
from_dict(data[, force])Loads class from data dictionary.
generate_t2_map([tissue, suppress_fat, ...])Generate 3D T2 map.
get_dimensions()Get shape of volumes.
get_metadata(key[, default])Get metadata for the scan.
load(path_or_data[, num_workers])Load scan.
load_custom_data(data, **kwargs)Recursively converts data to appropriate types.
save(path[, save_custom, image_data_format, ...])Saves scan data to disk with option for custom saving.
save_custom_data(metadata, paths[, fname_fmt])Finds all attributes of type MedicalVolume or Sequence/Mapping to MedicalVolume and saves them.
save_data(base_save_dirpath[, data_format])Deprecated: Alias for
self.save().segment(model, tissue[, use_rss])Segment tissue in scan.
to(device)Moves volumes of this scan onto the appropriate device.
Attributes
NAMEref_dicomThe reference dicom.