DeepTek employs Artificial Intelligence technology to alter screening operations and achieve superior outcomes while enabling significant cost reductions in this joint endeavor to eliminate Cardiomegaly. For example, DeepTeks’ technology automatically triages Cardiomegaly suspicions by analyzing Chest X-Rays in under a minute.
Cardiomegaly refers to the thickening of the heart muscles or the expansion of the chambers. Cardiomegaly is a sign of another heart issue, not a disease. Coronary artery disease is the most common cause.
Cardiomegaly can be caused by many conditions, including hypertension, coronary artery disease, infections, inherited disorders, and cardiomyopathies. Dilative cardiomyopathy: This type is characterized by a wide, poorly functioning left ventricle, which is the heart’s primary pumping chamber
Cardiomegaly is usually diagnosed subjectively. Two radiologists’ annotations can result in two different diagnoses, especially if the case is borderline. This necessitated developing an objective and automated approach for detecting Cardiomegaly, such as the cardiothoracic ratio (CTR). In a chest X-ray, this ratio is calculated by dividing the largest horizontal cardiac diameter by the largest horizontal thoracic diameter (measured between the inner borders of the ribs). Cardiomegaly is diagnosed when this ratio exceeds a certain threshold.
DeepTek employs Artificial Intelligence technology to alter screening operations and achieve superior outcomes while enabling significant cost reductions in this joint endeavour to eliminate Cardiomegaly. For example, DeepTeks’ technology automatically triages Cardiomegaly suspicions by analyzing Chest X-Rays in under a minute.
Mr Ajit Patil, Deeptek’s Co-Founder, stated, “To address the two stages of the cardiomegaly detection challenge, we constructed two neural network models. The first model discriminated between X-rays taken from the AP and PA perspectives. To calculate the CTR, the second model used the heart and thoracic diameters from the PA X-rays.”
Deeptek’s vision is to provide cutting-edge solutions based on deep learning algorithms to bridge the imaging sector’s wide gap. Bridging this gap will empower imaging experts, radiologists, physicians, patients, governmental decision-makers, and non-profit organizations with the ability to systematize imaging workflow dynamics.
