differenciating lung diseases
28 de June de 2022

Differentiating lung diseases with contextflow

contextflow SEARCH Lung CT, available in our AI marketplace for medical diagnosis, continues to prove useful in differentiating lung diseases.

The complexity of differentiating lung diseases

The complexity of differentiating lung diseases has made AI an increasingly important part of the diagnostic process. Examples include the Calw-Leonberg radiology group and the University of Innsbruck, which have already relied on contextflow’s tool.

Accurate diagnosis of lung diseases

CT offers added value in the diagnosis of lung diseases. While radiography provides a good, simple view of the lungs, CT provides high resolution in the submillimetre range to diagnose nodules, tumours, lesions and other pathologies.

Dr Scholz, a radiologist at the Calw-Leonberg group practice, stresses that lung diseases are still a big challenge and says that “the strength of AI is precisely to recognize patterns”, an area of the diagnostic process where contextflow’s software is of great value.


Contextflow SEARCH Lung CT allows radiologists to not only compare lung nodules with previous studies, but also to measure these nodules very accurately. It also assists in recognition and quantification of disease patterns related to interstitial lung diseases and COPD, which often blend and overlap on CT images, making diagnosis challenging.

It should be noted that many lung diseases lead to fibrosis and severe loss of lung function. It is now possible to treat some forms of fibrosis, but first an accurate diagnosis is necessary to optimally guide treatment decisions. In this sense, pattern recognition with AI tools such as contextflow SEARCH Lung CT greatly benefits the patient.

What is new in contextflow SEARCH Lung CT?

contextflow SEARCH Lung CT will soon incorporate a module that will go a step beyond listing lung findings: it will compare them over time and eventually suggest possible diagnoses based on the detected patterns.