OpenwaterHealth/OpenLIFU-python
Nov 2024 – Nov 2024
1 Month active
Languages Used
Python
Technical Skills
3D TransformationsAlgorithm DevelopmentCoordinate SystemsMedical ImagingNumerical Computation
Tong Fu
PROFILE
Tong Fu
Tong Fu developed a virtual fitting algorithm for MRI transducer pose optimization in the OpenwaterHealth/OpenLIFU-python repository. Using Python and leveraging skills in 3D transformations and numerical computation, Tong designed a method to compute the optimal transducer position and orientation for a given MRI volume and target. The approach included coordinate system conversions, pose computation, and target analysis within steering limits, iterating over a search grid to identify the best fit. This work automated and improved the accuracy of transducer placement, providing a robust foundation for future automation and quality assurance workflows in medical imaging applications. The implementation demonstrated technical depth.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
273
Activity Months1
Your Network
48 people
Work History
November 2024
1 Commits • 1 Features
Nov 1, 2024Month 2024-11 focused on delivering a critical feature in OpenwaterHealth/OpenLIFU-python: a virtual fitting algorithm for MRI transducer pose optimization. The work introduces a robust method to compute the optimal transducer transform (position and orientation) for a given MRI volume and target, including coordinate system conversions, pose computation, and target position analysis within steering limits. It iterates over a search grid to identify the best fit, enhancing automation and accuracy of transducer placement. Delivered in a single commit: 003b7034c93358650146b403b865eefe0eca7529 ("Implement virtual fitting algorithm (#147)").
1 Commits • 1 Features
Nov 1, 2024Month 2024-11 focused on delivering a critical feature in OpenwaterHealth/OpenLIFU-python: a virtual fitting algorithm for MRI transducer pose optimization. The work introduces a robust method to compute the optimal transducer transform (position and orientation) for a given MRI volume and target, including coordinate system conversions, pose computation, and target position analysis within steering limits. It iterates over a search grid to identify the best fit, enhancing automation and accuracy of transducer placement. Delivered in a single commit: 003b7034c93358650146b403b865eefe0eca7529 ("Implement virtual fitting algorithm (#147)").
November 2024
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance60.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
3D TransformationsAlgorithm DevelopmentCoordinate SystemsMedical ImagingNumerical Computation
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