XRMedix, Louisiana, United States
Keywords: Digital Health, Augmented Reality, Computer Vision, Medical Instrument Tracking, AI in HealthcareThe current standard of care for joint pain injections requires radiological (X-ray or ultrasound) guidance, limiting the scaling ability to meet the increasing demand. We introduce a cutting-edge solution, the Intelligent Needle Guidance System (INGS), a transformative technology that enables joint pain injections without radiological guidance. INGS addresses the soaring demand driven by increasing musculoskeletal injuries and aging and makes injections accessible without specialized facilities. We are developing advanced deep-learning models to conduct precise MRI data analysis that identifies musculoskeletal injuries and suggests an optimized injection path to reduce the risk of damage to critical internal structures like blood vessels. INGS then reconstructs MR images into photorealistic, patient-specific 3D models of the joint's internal structures, seamlessly integrating the deep learning model's needle path suggestions. During injection, the reconstructed 3D volume will be markerlessly projected onto the patient's body to guide the physician. We embed Fiber Bragg Grating (FBG) sensor technology into the needle and its stylet for real-time needle tracking and updating the projected 3D volume with the needle's current shape and position. This groundbreaking innovation ensures exceptional accuracy, even with ultra-thin needles, promising a new era of intra-articular (IA) injections.