Rutvik Dudhat

• Aim: Deep Learning–Based Automated Segmentation and Dynamic Analysis of the Fetal Bladder and Stomach in MRI. • Trained multi-class segmentation (bladder and stomach) models using nnUNet v2, achieved 0.70–0.85 Dice score. • Created ground truth masks through manual segmentation in ITK SNAP and optimized model performance using PyTorch and Python.

• Support medical device startups in implementing QMS, EU MDR, and EU AI Act compliance • Contribute to SaMD documentation and ISO 27001 alignment for data security • Develop regulatory templates and Moodle-based training modules on ISO 13485, QMS, and documentation processes

• Performed calibration, testing, and maintenance of medical devices including ventilators, patient monitor, ECGs, and other biomedical equipment • Gained knowledge of QMS under ISO 13485, MDR, CE and FDA regulatory environments

• Medical Imaging and data processing, MRI, AI in Medical Robotics • Biomedical Signal & Image Processing, Machine learning and AI • Regulatory Affairs, Quality management

• Biomechanics and Bio signals, Diagnostic Instrumentation • Regulatory Standards for Medical Devices (MDR, FDA, CE), Medical Imaging Techniques, Quality Assurance