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]¶: Initialize self. See help(type(self)) for accurate signature.

Methods

`__init__`(volumes)	Initialize self.
`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.

Attributes

`NAME`
`ref_dicom`	The reference dicom.