ophth_ds_types
Types for ophthalmology data sources.
Classes
DICOMImage
class DICOMImage( AcquisitionDeviceTypeCodeSequence: collections.abc.Sequence[bitfount.data.datasources.ophthalmology.ophth_ds_types._AcquisitionDeviceTypeCodeSequenceElement], PatientName: str, PatientBirthDate: str, AcquisitionDateTime: str, ImageLaterality: str, NumberOfFrames: int,):Named tuple for a DICOM image.
Variables
AcquisitionDateTime : str- Alias for field number 3
AcquisitionDeviceTypeCodeSequence : collections.abc.Sequence[bitfount.data.datasources.ophthalmology.ophth_ds_types._AcquisitionDeviceTypeCodeSequenceElement]- Alias for field number 0
ImageLaterality : str- Alias for field number 4
NumberOfFrames : int- Alias for field number 5
PatientBirthDate : str- Alias for field number 2
PatientName : str- Alias for field number 1
FunctionalGroupsSequenceField
class FunctionalGroupsSequenceField( name: Literal['Shared Functional Groups Sequence', 'Per-Frame Functional Groups Sequence'], value: list[bitfount.data.datasources.ophthalmology.ophth_ds_types._FunctionalGroupsSequenceFieldElement],):Named tuple for Functional Groups Sequence Fields.
Applies to Shared Functional Groups Sequence (5200, 9229) and Per-Frame Functional Groups Sequence (0028, 9230).
Arguments
name: The name of the sequence field.value: The value of the sequence field.
Variables
name : Literal['Shared Functional Groups Sequence', 'Per-Frame Functional Groups Sequence']- Alias for field number 0
value : list[bitfount.data.datasources.ophthalmology.ophth_ds_types._FunctionalGroupsSequenceFieldElement]- Alias for field number 1
FunctionalGroupsSequenceProcessingOutput
class FunctionalGroupsSequenceProcessingOutput(*args, **kwargs):dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object's (key, value) pairs dict(iterable) -> new dictionary initialized as if via: d = for k, v in iterable: d[k] = v dict(**kwargs) -> new dictionary initialized with the name=value pairs in the keyword argument list. For example: dict(one=1, two=2)
Variables
- static
Pixel Spacing Column : float
- static
Pixel Spacing Row : float
- static
Slice Thickness : float
Metadata
class Metadata(*args, **kwargs):The initial JSON output of from parsing a single ophthalmology file.
Variables
- static
exam : bitfount.data.datasources.ophthalmology.ophth_ds_types._ExamInfo
- static
images : bitfount.data.datasources.ophthalmology.ophth_ds_types._ImagesInfo
- static
patient : bitfount.data.datasources.ophthalmology.ophth_ds_types._PatientInfo
- static
series : bitfount.data.datasources.ophthalmology.ophth_ds_types._SeriesInfo
ProcessedDICOMImage
class ProcessedDICOMImage( file_name: str, modality: Literal['OCT', 'SLO', None], patient_key: str, acquisition_datetime: Optional[datetime.datetime],):Named tuple for a processed DICOM image.
Variables
acquisition_datetime : Optional[datetime.datetime]- Alias for field number 3
file_name : str- Alias for field number 0
modality : Literal['OCT', 'SLO', None]- Alias for field number 1
patient_key : str- Alias for field number 2
ProcessedDataRequiredTypes
class ProcessedDataRequiredTypes(*args, **kwargs):The final output of the processing from a single ophthalmology file.
Variables
- static
Acquisition DateTime : Union[str, pandas._libs.tslibs.timestamps.Timestamp]
- static
Columns : int
- static
Manufacturer : str
- static
Manufacturer's Model Name : str
- static
Number of Frames : int
- static
Patient ID : str
- static
Patient's Birth Date : Union[str, pandas._libs.tslibs.timestamps.Timestamp]
- static
Patient's Name : str
- static
Patient's Sex : str
- static
Pixel Spacing Column : float
- static
Pixel Spacing Row : float
- static
Rows : int
- static
Scan Laterality : str
- static
Slice Thickness : float
- static
Study Date : Union[str, pandas._libs.tslibs.timestamps.Timestamp]
- static
date_of_birth : str
- static
dimensions_mm_depth : float
- static
dimensions_mm_height : float
- static
dimensions_mm_width : float
- static
first_name : str
- static
fixation : str
- static
gender : str
- static
group_id : int
- static
images : list[str]
- static
last_name : str
- static
laterality : str
- static
num_bscans : int
- static
num_modalities : int
- static
patient_key : str
- static
photo_locations_end_x : list[float]
- static
photo_locations_end_y : list[float]
- static
photo_locations_start_x : list[float]
- static
photo_locations_start_y : list[float]
- static
protocol : str
- static
resolutions_mm_depth : float
- static
resolutions_mm_height : float
- static
resolutions_mm_width : float
- static
scan_datetime : str
- static
scanner_model : str
- static
size_height : int
- static
size_width : int
- static
slo_dimensions_mm_height : float
- static
slo_dimensions_mm_width : float
- static
slo_images : list[str]
- static
slo_size_height : int
- static
slo_size_width : int
- static
source_info : str
ProcessedDataRequiredTypesDICOM
class ProcessedDataRequiredTypesDICOM(*args, **kwargs):dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object's (key, value) pairs dict(iterable) -> new dictionary initialized as if via: d = for k, v in iterable: d[k] = v dict(**kwargs) -> new dictionary initialized with the name=value pairs in the keyword argument list. For example: dict(one=1, two=2)
Variables
- static
Acquisition DateTime : Union[str, pandas._libs.tslibs.timestamps.Timestamp]
- static
Columns : int
- static
Manufacturer : str
- static
Manufacturer's Model Name : str
- static
Number of Frames : int
- static
Patient ID : str
- static
Patient's Birth Date : Union[str, pandas._libs.tslibs.timestamps.Timestamp]
- static
Patient's Name : str
- static
Patient's Sex : str
- static
Pixel Spacing Column : float
- static
Pixel Spacing Row : float
- static
Rows : int
- static
Scan Laterality : str
- static
Slice Thickness : float
- static
Study Date : Union[str, pandas._libs.tslibs.timestamps.Timestamp]