dosma.scan_sequences.Mapss¶

class dosma.scan_sequences.Mapss(volumes: Sequence[dosma.core.med_volume.MedicalVolume], echo_times: Optional[Sequence[float]] = None)[source]¶

MAPSS MRI sequence.

Magnetization‐prepared angle‐modulated partitioned k‐space spoiled gradient echo snapshots (3D MAPSS) is a spoiled gradient (SPGR) sequence that reduce specific absorption rate (SAR), increase SNR, and reduce the extent of retrospective correction of contaminating T1 effects.

The MAPSS sequence can be used to estimate both T1𝜌 and T2 quantitative values. MAPSS scans must also be intra-registered to ensure alignment between all volumes acquired at different echos and spin-lock times. Intra-registration is performed automatically upon construction. \(T_2\) and :T_{1rho} fitting is also supported.

References

X Li, ET Han, RF Busse, S Majumdar. In vivo t1ρ mapping in cartilage using 3d magnetization-prepared angle-modulated partitioned k-space spoiled gradient echo snapshots (3d mapss). Magnetic Resonance in Medicine, 59(2):298–307 (2008).

__init__(volumes: Sequence[dosma.core.med_volume.MedicalVolume], echo_times: Optional[Sequence[float]] = None)[source]¶: Initialize self. See help(type(self)) for accurate signature.

Methods

`__init__`(volumes[, echo_times])	Initialize self.
`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_t1_rho_map`([tissue, mask_path, …])	Generate 3D T1-rho map and r-squared fit map using mono-exponential fit across subvolumes acquired at different echo times.
`generate_t2_map`([tissue, mask_path, num_workers])	Generate 3D T2 map and r-squared fit map using mono-exponential fit across subvolumes acquired at different echo times.
`get_dimensions`()	Get shape of volumes.
`get_metadata`(key[, default])	Get metadata for the scan.
`intraregister`()	Intra-register volumes.
`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()`.

Attributes

`NAME`
`ref_dicom`	The reference dicom.