AI-Powered Medical Imaging
The imaging system is built on deep convolutional neural networks trained on tens of millions of labelled medical images, spanning radiology, pathology, dermatology, and ophthalmology.
The models identify findings with a precision that surpasses unaided human review, detecting abnormalities that are easily missed during high-volume clinical reading.
- Tumour detection in CT and MRI with sub-millimetre precision
- Fracture identification in X-ray across all skeletal regions
- Diabetic retinopathy screening from retinal photographs
- Skin lesion classification and melanoma detection
From Scan to Report in Thirty Seconds
The engine delivers a complete preliminary analysis in under thirty seconds, flagging critical findings, measuring abnormalities, and generating structured reports for clinician review.
Every analysis is traceable and explainable, with highlighted regions of interest, and is designed to support rather than replace the clinician's final judgement.
- Automatic lesion segmentation and dimensional measurement
- Priority flagging of urgent and critical findings
- Side-by-side comparison with prior imaging studies
- Full integration with existing imaging systems
Applications in Clinical Practice
Detection of pulmonary nodules in chest CT at an early, treatable stage.
Identification of intracranial bleeding with immediate neurosurgical alert.
Automated screening for diabetic retinopathy and glaucoma at scale.
Detection of hairline fractures missed in high-volume readings.
Analysis of biopsy slides to detect and grade cancer cells.
Assessment of echocardiograms and cardiac MRI for abnormalities.
Deploy Computer Vision in Your Hospital
Contact Eeswar Makineni to explore how this capability can transform your hospital.