Cortechs.ai delivers AI‑driven brain segmentation and quantitative imaging tools that help clinicians visualize lesions, track volumetric changes, and automate radiology workflows for neurological and oncological diseases. Their software provides automated tracer activity quantification, CT alignment, and prostate MRI optimization, enabling fast, accurate diagnosis and longitudinal tracking of FLAIR, T2 GRE, and SWI lesions. The platform is used by over 1,500 medical institutions in 44 countries, having scanned more than 2 million brains.
Funding
Funding not disclosed
Founders
Product
Problem
Radiologists and oncologists must manually segment brain lesions and quantify tumor volumes from MRI and CT scans, a time‑consuming process prone to variability and limited by the need for expert interpretation.
Solution
Cortechs offers AI‑driven software that automatically segments brain structures, quantifies lesion volumes, and tracks changes across longitudinal scans. The platform aligns CT images, measures tracer activity, and provides 3‑D pre‑ and post‑operative tumor analyses, delivering consistent quantitative metrics. Integrated workflows streamline radiology operations, allowing clinicians to assess disease progression and treatment response more efficiently. Results are presented with visual overlays and volumetric reports that can be compared against a large database of normal controls. The solution supports multiple MRI sequences, including FLAIR, T2*GRE, and SWI, enhancing detection of diverse neurological pathologies.
Target Audience
Primary customers are radiology departments, neuro‑oncology clinics, and imaging centers that require precise, repeatable brain lesion quantification for diagnosis, treatment planning, and outcome monitoring.
Features
- Deep‑learning brain segmentation delivering voxel‑level lesion delineation across MRI and CT modalities
- Automated volumetric analysis for pre‑ and post‑operative tumor assessment with 3‑D visualizations
- CT alignment and tracer activity quantification to accelerate diagnostic interpretation
- Longitudinal tracking of FLAIR, T2*GRE, and SWI lesions for monitoring disease progression
- Cloud‑based reporting dashboard with quantitative metrics and comparison to normative databases
- Integration with existing radiology PACS and workflow systems for seamless adoption