DICOM files parser meant to facilitate data access.
Project description
dicom_parser
dicom_parser is a utility python package meant to facilitate access to DICOM header information by extending the functionality of pydicom.
Essentially, dicom_parser uses DICOM's data-element value-representation (VR), as well as prior knowledge on vendor-specific private tags or encoding schemes, in order to transform them to more "pythonic" data structures when possible.
For more information, please see the documentation.
Installation
To install the latest version of dicom_parser
, simply run:
pip install dicom_parser
Quickstart
The most basic usage case is reading a single DICOM image (.dcm file) as an Image instance.
from dicom_parser import Image
# Create a DICOM Image object
image = Image('/path/to/dicom/file.dcm')
Coversion to Python's native types
dicom_parser provides dict-like access to the parsed values of the header's data-elements. The raw values as read by pydicom remain accessible through the raw attribute.
Examples
Decimal String (DS) to float using the Header class's get method:
raw_value = image.header.raw['ImagingFrequency'].value
raw_value
>> "123.25993"
type(raw_value)
>> str
parsed_value = image.header.get('ImagingFrequency')
parsed_value
>> 123.25993
type(parsed_value)
>> float
Age String (AS) to float:
raw_value = image.header.raw['PatientAge'].value
raw_value
>> "027Y"
type(raw_value)
>> str
parsed_value = image.header.get('PatientAge')
parsed_value
>> 27.0
type(parsed_value)
>> float
Date String (DA) to datetime.date using the Header class's indexing operator/subscript notation:
raw_value = image.header.raw['PatientBirthDate'].value
raw_value
>> "19901214"
type(raw_value)
>> str
parsed_value = image.header['PatientBirthDate']
parsed_value
>> datetime.date(1990, 12, 14)
type(parsed_value)
>> datetime.date
Et cetera.
The dict-like functionality also includes safe getting:
image.header.get('MissingKey') >> None image.header.get('MissingKey', 'DefaultValue') >> 'DefaultValue'As well as raising a KeyError for missing keys with the indexing operator:
image.header['MissingKey'] >> ... >> KeyError: "The keyword: 'MissingKey' does not exist in the header!"
Read DICOM series directory as a Series
Another useful class this package offers is the Series class:
from dicom_parser import Series
series = Series('/path/to/dicom/series/')
# Read stacked pixel arrays as a 3D volume
type(series.data)
>>> numpy.ndarray
series.data.shape
>> (224, 224, 208)
# Access the underlying Image instances
series.images[6].header.get('InstanceNumber')
>> 7 # instance numbers are 1-indexed
Reading Siemens 4D data encoded as mosaics is also supported:
fmri_series = Series('/path/to/dicom/fmri/')
fmri_series.data.shape
>> (96, 96, 64, 200)
For more information, please see the documentation.
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