Volumetric Segmentation of Cardiac Images

Case ID:

This invention is a semi-automated segmentation method and system which significantly reduces the amount of time and expertise required by an operator and also improves accuracy and repeatability. While the inventors have implemented this approach specifically for segmentation of right ventricles in 4D images, this invention is adaptable to a wide range of other medical imaging and other application areas. The user only selects a few landmarks, rather than entire contours, and then the remaining segmentation and related analytics are performed automatically. By minimizing user input and eliminating the need for training data, this new invention can reduce imaging time and, in the case of the current cardiac implementation, shift much of the workload from radiologists to technicians.



There are a number of limitations of current segmentation algorithms when dealing with complex images over time. Dynamic programming can manage some of these shortcomings but that approach creates new challenges including the need to conduct training for each segmentation analysis as well as managing errors introduced with multi-point shape intersections. Current cardiac segmentation techniques require the user to manually outline the ventricle and then use training data to mimic the movement throughout the cardiac phase. They also use shape models, which reduce accuracy and, in particular, the ability to segment pathological cases.



  • Right ventricle and other medical image segmentation
  • Segmentation of complex shapes using landmarks
  • Time-series image segmentation
  • Other image segmentation applications


  • Shift segmentation input to technicians
  • Reduce input time by 10x
  • Improved accuracy and repeatability
  • Enhanced analytics

Status: issued U.S. patent #10,204,413

Patent Information:
Contact For More Information:
Tariq Ahmed
Sr Licensing Manager, College of Engineering
The University of Arizona
Lead Inventor(s):
Jose Rosado-Toro
Jeffrey Rodriguez
Ryan Avery
Aiden Abidov