Difference between revisions of "2016 Summer Project Week/Guided Ultrasound Calibration"
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* Elvis Chen (Robarts Research Institute) | * Elvis Chen (Robarts Research Institute) | ||
* Adam Rankin (Robarts Research Institute) | * Adam Rankin (Robarts Research Institute) | ||
| + | * Tamas Ungi (Queen's University) | ||
==Background== | ==Background== | ||
| − | Ultrasound probe calibration is an active area of research, with many calibration phantoms and numerical | + | Ultrasound probe calibration is an active area of research, with many calibration phantoms and their numerical solutions available in the current literature. In the upcoming IPCAI (2016) conference, we present the first ultrasound calibration framework that provides real-time Target Registration Error (TRE) feedback. That is, between successive measurement, our framework suggests the end-user where and how in the US image to collect next phantom measurement so that the TRE is maximally minimized. Refer to the following paper for a detailed description: |
* IJCARS Paper: http://link.springer.com/article/10.1007/s11548-016-1390-7 | * IJCARS Paper: http://link.springer.com/article/10.1007/s11548-016-1390-7 | ||
| Line 19: | Line 20: | ||
The US calibration is modeled as point-line registration. | The US calibration is modeled as point-line registration. | ||
| + | |||
| + | Refer to the following video for a demonstration based on the current C++/standalone implementation: | ||
| + | [[IPCAI_edited.mp4]] | ||
==Project Description== | ==Project Description== | ||
| Line 30: | Line 34: | ||
* Use PLUS library for data (US image and tracker transforms) acquisition | * Use PLUS library for data (US image and tracker transforms) acquisition | ||
* port existing C++/VTK code into the slicer environment | * port existing C++/VTK code into the slicer environment | ||
| + | * There are 2 parts to the development: | ||
| + | ** The GUI for the calibration | ||
| + | *** use python for GUI development? | ||
| + | ** TRE prediction | ||
| + | *** use numpy for the math. HOWEVER, we need multi-threading | ||
| + | *** alternatively, we can write a CLI module for the computation | ||
</div> | </div> | ||
<div style="width: 27%; float: left; padding-right: 3%;"> | <div style="width: 27%; float: left; padding-right: 3%;"> | ||
<h3>Progress</h3> | <h3>Progress</h3> | ||
* Slicer development has been properly set up. | * Slicer development has been properly set up. | ||
| + | * We ended up developing a python loadable module based on Adam Rankin's prior work, which has a simple/nice interface to fiducial collection as well as OpenIGTLink. | ||
| + | * There are 2 parts to our calibration framework: | ||
| + | ** calibration, and | ||
| + | ** guidance for calibration based on Target Registration Error, which is computational intensive, and not strictly needed for probe calibration. | ||
| + | Thus the calibration portion will be integrated by the end of the project week, while TRE guidance will be integrated later (requiring multi-threading). | ||
</div> | </div> | ||
</div> | </div> | ||
Latest revision as of 14:44, 24 June 2016
Home < 2016 Summer Project Week < Guided Ultrasound Calibration
Key Investigators
- Elvis Chen (Robarts Research Institute)
- Adam Rankin (Robarts Research Institute)
- Tamas Ungi (Queen's University)
Background
Ultrasound probe calibration is an active area of research, with many calibration phantoms and their numerical solutions available in the current literature. In the upcoming IPCAI (2016) conference, we present the first ultrasound calibration framework that provides real-time Target Registration Error (TRE) feedback. That is, between successive measurement, our framework suggests the end-user where and how in the US image to collect next phantom measurement so that the TRE is maximally minimized. Refer to the following paper for a detailed description:
Both theoretical experimental results suggest that sub-millimetre TRE can be achieved with 12 measurements.
The TRE prediction is based on spatial stiffnessm model.
The US calibration is modeled as point-line registration.
Refer to the following video for a demonstration based on the current C++/standalone implementation: IPCAI_edited.mp4
Project Description
Objective
- A slicer module/GUI for US calibration
Approach, Plan
- Use PLUS library for data (US image and tracker transforms) acquisition
- port existing C++/VTK code into the slicer environment
- There are 2 parts to the development:
- The GUI for the calibration
- use python for GUI development?
- TRE prediction
- use numpy for the math. HOWEVER, we need multi-threading
- alternatively, we can write a CLI module for the computation
- The GUI for the calibration
Progress
- Slicer development has been properly set up.
- We ended up developing a python loadable module based on Adam Rankin's prior work, which has a simple/nice interface to fiducial collection as well as OpenIGTLink.
- There are 2 parts to our calibration framework:
- calibration, and
- guidance for calibration based on Target Registration Error, which is computational intensive, and not strictly needed for probe calibration.
Thus the calibration portion will be integrated by the end of the project week, while TRE guidance will be integrated later (requiring multi-threading).
