Tech Tips: DICOM Image Caching with Redis

Summary

This post covers a demonstration of the usage of Redis for caching DICOM imagery. I use a Jupyter Notebook to step through loading and searching DICOM images in a Redis Enterprise environment.

Architecture

Redis Enterprise Environment

Screen-shot below of the resulting environment in Docker.

Sample DICOM Image

I use a portion of sample images included with the Pydicom lib. Below is an example:

Code Snippets

Data Load

The code below loops through the Pydicom-included DICOM files. Those that contain the meta-data that is going to be subsequently used for some search scenarios are broken up into 5 KB chunks and stored as Redis Strings. Those chunks and the meta-data are then saved to a Redis JSON object. The chunks' Redis key names are stored as an array in that JSON object.

	def load_chunks(key, file, chunk_size):
	i = 0
	chunk_keys = []
	with open(file, 'rb') as infile:
	while chunk := infile.read(chunk_size):
	chunk_key = f'chunk:{key}:{i}'
	client.set(chunk_key, chunk)
	chunk_keys.append(chunk_key)
	i += 1
	return chunk_keys

	count = 0
	pydicom.config.settings.reading_validation_mode = pydicom.config.RAISE
	for file in pydicom.data.get_testdata_files():
	try:
	ds = pydicom.dcmread(file)
	key = f'file:{os.path.basename(file)}'
	image_name = os.path.basename(file)
	protocol_name = re.sub(r'\s+', ' ', ds.ProtocolName)
	patient_sex = ds.PatientSex
	study_date = ds.StudyDate
	manufacturer = ds.Manufacturer.upper()
	chunk_keys = load_chunks(key, file, CHUNK_SIZE)

	client.json().set(key, '$', {
	'imageName': image_name,
	'protocolName': protocol_name,
	'patientSex': patient_sex,
	'studyDate': study_date,
	'manufacturer': manufacturer,
	'chunks': chunk_keys
	})
	count += 1
	except:
	pass
	print(f'Files loaded: {count}')

view raw dicom-dataload.py hosted with ❤ by GitHub

Search Scenario 1

This code retrieves all the byte chunks for a DICOM image where the Redis key is known. Strictly, speaking this isn't a 'search'. I'm simply performing a JSON GET for a key name.

	file_name = 'JPGExtended.dcm'
	t1 = perf_counter()
	results = client.json().get(f'file:{file_name}', '$.chunks')
	total_bytes = get_bytes(results[0])
	t2 = perf_counter()
	print(f'Exec time: {round((t2-t1)*1000,2)} ms')
	print(f'Bytes Retrieved: {len(total_bytes)}')

view raw dicom-jsonget.py hosted with ❤ by GitHub

Search Scenario 2

The code below demonstrates how to put together a Redis Search on the image meta-data. In this case, we're looking for a DICOM image with a protocolName of 194 and studyDate in 2019.

	query = Query('@protocolName:194 @studyDate:{2019*}')\
	.return_field('$.chunks', as_field='chunks')\
	.return_field('$.imageName', as_field='imageName')
	t1 = perf_counter()
	result = client.ft('dicom_idx').search(query)
	total_bytes = bytearray()
	if len(result.docs) > 0:
	total_bytes = get_bytes(json.loads(result.docs[0].chunks))
	t2 = perf_counter()

	print(f'Exec time: {round((t2-t1)*1000,2)} ms')
	print(f'Image name: {result.docs[0].imageName}')
	print(f'Bytes Retrieved: {len(total_bytes)}')

view raw dicom-search2.py hosted with ❤ by GitHub

Source

https://github.com/Redislabs-Solution-Architects/redis-dicom

Sunday, November 19, 2023

DICOM Image Caching with Redis