3D Reconstruction Engineer

3 days ago


Minneapolis, Minnesota, United States AngioInsight Full time

We are seeking a skilled 3D Reconstruction Engineer to enhance our cardiology capabilities. In this role, you will be responsible for developing and optimizing 3D models of blood vessels from angiogram image data, contributing to innovative solutions in medical imaging.

Key Responsibilities

  • Develop and optimize algorithms for 3D reconstruction of blood vessels from medical imaging, such as coronary angiograms.
  • Implement point cloud-based reconstruction techniques for modeling complex vessel geometries.
  • Lead the transition from point cloud and deterministic methods to advanced machine learning techniques, integrating neural networks, deep learning, and generative models to improve 3D reconstructions.
  • Research and apply state-of-the-art machine learning techniques, such as Generative Adversarial Networks (GANs) or autoencoders, to model vessel geometries more accurately and efficiently.
  • Collaborate with cross-functional teams to ensure smooth integration of new reconstruction methods into AngioInsight's diagnostic software.
  • Scale the 3D reconstruction pipeline using AI-driven techniques, particularly as the dataset grows in size and complexity.
  • Enhance the performance and accuracy of existing 3D models using machine learning-based refinements.
  • Conduct research on emerging trends in AI-driven 3D modeling and medical imaging to continuously evolve the reconstruction techniques.

Requirements

  • Bachelor's or Master's degree in Computer Science, Biomedical Engineering, Applied Mathematics, Robotics, or related field.
  • Experience in Robotics, SLAM, SfM, or stereo vision.
  • Proven experience with 3D reconstruction techniques, particularly point clouds, and geometry representation methods.
  • Strong background in machine learning techniques, particularly neural networks, deep learning, and generative models.
  • Proficiency in programming languages such as Python, C++, or MATLAB, and experience with machine learning frameworks like PyTorch or TensorFlow.
  • Experience with medical imaging data (e.g., DICOM, angiograms) and working in the healthcare/medical technology space is a strong plus.
  • Strong problem-solving skills with the ability to transition from deterministic methods to machine learning approaches.
  • Excellent communication and teamwork skills to collaborate with cross-disciplinary teams, including data scientists, software engineers, and clinicians.


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