Industrialitzation of healthcare services

Radiology workflows

Radiology workflows

For an average 20% of computed tomography and magnetic resonance images, radiologists see structure (pathology) with which they are not familiar. The process of finding information in order to write a report takes up to 20 minutes. There is a significant variation in the identification of pathologies in the same images by multiple radiologists leaving patients with different diagnosis for the same image.

Unfamiliar structure

for 20% of images


20 minutes to find information

Different diagnosis

for the same image

Led by contextflow GmbH, the pilot aims to reduce the time of diagnosis in radiology departments, and at the same time the quality of diagnosis by providing an efficient search engine for radiological data.

Why a big data approach is needed

Finding relevant cases during search is a big data problem because of the high variability in natural anatomy and disease markers, the steady stream of new data and the need for fast access to the knowledge encoded in these cases during daily diagnosis. The technologies employed are deep learning, extremely large-scale image indexing and similarity search, semantic analysis of text in radiology reports and text search.

Hospital U Puerta Hierro SERMAS


Pilot 12: Radiology workflows


Poster at BigMedilytics event: “Big Data: Fueling the transformation of Europe’s Healthcare Sector”. September 4-5, 2019, Valencia, Spain