Automated Artificial Intelligence generating Patient-Specific dynamic 3D cardiac models.
These models are key to personalized digital analysis.
MYOCARDIAK is dedicated to reducing the burden on the healthcare system, while lowering cost through the use of personalized digital cardiac models.
CURENT PROTOCOLS We work with current MRI and CT clinical protocols - there is no change in the workflow.
PATIENT-SPECIFIC From the clinical images, we build a patient-specific cardiac digital twin using Artificial Intelligence.
BIOPHYSIOLOGICAL We extract the biophysiological features from the patient-specific models,
DEEP LEARNING We harness the power of Deep Learning to analyze the geometrical 3D models along with the biophysiological features to report established clinical metrics relating to population data.
CLINICAL USE Clinical metrics extracted from the models, aid in the clinical decision making.
Automatic inspection, AI segmentation, artefacts correction, and generation of 3D/4D models
Clinical metrics are extracted automatically from the digital models allowing for easy clinical analysis
Clinicians upload anonymized MRI or CT images
Models are returned along with the computed metrics. Clinicians can check the outputs on their desktop or mobile
Clinicians gain advanced information on patient's personalized morphology and clinical metrics, aiding the decision making process
Considerable time is saved through our automated approach, allowing for a higher throughput of patients, in a smarter way
Treatment evaluation can be performed using the models allowing for a cost-effective assessment of the treatment plan
Identification of individuals more prone to benefit from cardiac rehabilitation programs can be obtained from individuals' computed health outcomes
- Currently only for use for Investigational and Research Purposes -
By 2035, 8 million adults living in the United States will have heart failure, costing a projected $1 trillion*
*American Heart Association