PRECIMON is a Class-II medical device (software as a medical device) which is used in conjunction with a bronchoscopy unit. By providing a patient’s Computerized Tomography (CT) images and bronchoscopy camera feed, it is able to localize the target lesion and support early diagnosis of suspicious lesions with almost 100% accuracy. In order to detect and take samples from a target lesion, their software transforms CT images into virtual 3D airway and blood vessel volumes and then the system asks the operator to mark the lesion on a user interface. Please click to view PRECIMON CE Certificate.

The system then calculates the safest route to the lesion in order to eliminate risks of bleeding inside lungs. The calculated route is then shown on both virtual and real bronchoscopy video frames to lead the operating physician into the lesion. With this device, the operator will be able to see where the lesion is and with which angle the bronchoscopic needle should take a sample.

Lung masses are observed in chest computerized tomographies (CT). Doctors don’t know the exact diagnosis until they send the nodules for pathology, and they need to take biopsies from these nodules to diagnose them by either lung endoscopy (bronchoscopy) or by CT needle biopsy. Not all lung nodules are accessible due either to size or location. Doctors generally decide to keep a watchful eye on the lesion through regular chest CT’s or surgically removing the lesion if it starts to increase in size. If the doctor decides not to act immediately, the patient may lose valuable time if the lesion is cancerous. If the doctor decides to operate immediately, the patient may benefit if the lesion is cancerous and it is removed. However, if the lesion is not malignant, the patient has undergone an unnecessary surgery.

Physicians need a better way of diagnosing lung lesions. Through ELAA Technology’s artificial intelligence-based three-dimensional lung navigation algorithm, doctors can easily reach potentially dangerous lung lesions without the difficulties they currently face in current methods of lung cancer diagnostics.

High Accuracy
98% accuracy on
hitting the tumor.

No Bleeding
No Risk of abundant

No Capex
No need for equipment

Early Diagnosis
Higher survival

Early Diagnosis
Reduced healthcare

Easy to manage
diagnosis process.

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