CT Scan

DATA PIPELINE

The data pipeline architecture is built using datasets of images to detect critical abnormalities such as a bleed, fracture, mass effect, or midline shift in the CT scans for priority review. Advanced data workflow and visualization tools are integrated into the pipeline to ensure that the right datasets are sent for training the algorithms.

TRAINING PIPELINE

Wavelabs Insight algorithms are built on deep neural networks like 3D Convolutional Neural Networks and trained using large sets of CT scan images. The algorithms are device-agnostic, i.e, they work with non-contrast scans from all major CT scan manufacturers, and can provide quick results.

INFERENCE PIPELINE

The framework provides for automatic post-processing of imaging datasets. It supports the interpretation of the data by automatically providing results of its analysis for review, confirmation, and possible inclusion in the final report or care pathway, raising the precision and ensuring high-quality outcomes in diagnostic decision-making.

MONITORING AND LOGGING

Wavelabs Insight also provides for real-time quantification and progression monitoring services within its framework. It provides for fully automated detection, quantification, and visualization of key metrics at each step of the process.