Client Story: AI segmentation of anatomical structures with apoQlar

Revolutionizing Medical Imaging with AI Segmentation with apoQlar VSI HoloMedicine®

Client Story – AI segmentation in healthcare with apoQlar

About the Project

apoQlar, the creator of the VSI HoloMedicine® platform, utilizes Microsoft HoloLens 2 hardware to transform medical images, clinical workflows, and medical education into a cutting-edge 3D mixed reality environment. With a focus on surgical planning activities and patient education, apoQlar aims to provide surgeons with precise anatomical structures and enhance the understanding of planned surgeries through real patient data.


Integrating AI into medical devices for purposes beyond research necessitates compliance with medical certifications and regulatory requirements. Robust documentation and reproducibility of AI models are essential, covering areas such as data management, model training and tuning, evaluation, and deployment. Adhering to these standards, our models are built on the trusted frameworks of Microsoft Azure Machine Learning and Microsoft InnerEye, ensuring comprehensive documentation of dataset characteristics, training procedures, results, and achieved metrics.


In collaboration with apoQlar experts and medical professionals specializing in various fields, we developed a series of AI models specifically designed for segmenting different anatomical structures based on Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). The AI models successfully identify structures such as bones, vessels, and brain parts like ventricles. Leveraging state-of-the-art neural network architectures, including variations of the U-Net architecture, our models consistently deliver exceptional segmentation results.

AI Segmentation
Fig.: Segmentation of anatomical structures on MRI/CT scans

Business Benefits:

  • Precise Anatomical Segmentation: The AI models accurately segment and identify complex anatomical structures, providing surgeons with detailed information for surgical planning and enhancing patient education.
  • Enhanced Surgical Planning: Surgeons can visualize patient-specific anatomical structures in a 3D mixed reality environment, enabling better surgical preparation and decision-making.
  • Improved Patient Education: The immersive 3D visualization of anatomical structures aids in explaining planned surgeries to patients, fostering better understanding and informed consent.
  • Time and Cost Savings: AI segmentation significantly reduces the manual effort required for segmenting anatomical structures, streamlining clinical workflows, and potentially reducing costs.
  • Integration with VSI HoloMedicine®: The AI models seamlessly integrate with apoQlar’s VSI HoloMedicine® platform, enhancing the overall user experience and expanding the capabilities of medical imaging technologies.

Solution’s Unique Features:

  • Cutting-Edge AI Models: Developed using state-of-the-art neural network architectures, our AI models achieve superior results in anatomical segmentation.
  • Expert Collaboration: Close collaboration with apoQlar experts and medical professionals ensures the models’ accuracy and relevance for surgical planning and patient education.
  • Compliance and Documentation: Built on MS Azure Machine Learning and MS InnerEye, our models adhere to regulatory standards, providing robust documentation and reproducibility.

The partnership between apoQlar and our team has revolutionized medical imaging by leveraging advanced AI models for precise segmentation of anatomical structures. The VSI HoloMedicine® platform combined with our state-of-the-art neural network architectures delivers unparalleled results, empowering surgeons with detailed insights and improving patient education. By integrating AI into medical devices, we enhance surgical planning, streamline workflows, and pave the way for transformative advancements in medical imaging technologies.

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