Artificial Intelligence Engineer – Medical Image Annotation and Segmentation
Segmentation
I performed extensive annotation and segmentation of MRI brain structures for AI-driven medical imaging applications. I developed and managed medical image data pipelines including data collection, annotation, preprocessing, augmentation, and dataset engineering. I collaborated with research teams to ensure clinical reliability and accuracy in model training and validation. • Applied deep learning architectures such as U-Net and Mask R-CNN for segmentation. • Used Python, TensorFlow, and Keras for annotation, processing, and workflow automation. • Focused on challenges of small dataset AI optimization and generalization in medical imaging. • Ensured compliance with MRI safety and clinical standards throughout all data labeling processes.
I performed extensive annotation and segmentation of MRI brain structures for AI-driven medical imaging applications. I developed and managed medical image data pipelines including data collection, annotation, preprocessing, augmentation, and dataset engineering. I collaborated with research teams to ensure clinical reliability and accuracy in model training and validation. • Applied deep learning architectures such as U-Net and Mask R-CNN for segmentation. • Used Python, TensorFlow, and Keras for annotation, processing, and workflow automation. • Focused on challenges of small dataset AI optimization and generalization in medical imaging. • Ensured compliance with MRI safety and clinical standards throughout all data labeling processes.
2021 - Present