L&T Technology Services (LTTS) is launching its AI-powered digital-twin platform for lung navigation, surgical planning, and respiratory diagnostics.
The platform integrates with CT imaging workflows and uses deep-learning models to reconstruct 3D digital twins of the lungs, enabling visualization of airways, blood vessels, lung lobes, and lesions, according to the company. It supports bronchoscopy and biopsy planning by allowing clinicians to simulate procedural pathways in a patient-specific anatomical model, LTTS said.
The new platform includes automated segmentation, volumetric analysis, and navigation path planning.
The company noted that the platform has been built on NVIDIA infrastructure, including Omniverse and OpenUSD for 3D visualization, TensorRT for AI inference, and MONAI for medical image segmentation.
No regulatory clearance has been announced yet for the platform, which debuted at RSNA in December.
![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&dpr=2&fit=crop&h=167&q=70&w=250)
