Difference between revisions of "Project Week 25/Wrist Kinematics:"

Revision as of 09:48, 30 June 2017

Home < Project Week 25 < Wrist Kinematics:

Objective	Approach and Plan	Progress and Next Steps
The clinical goal of this project is the use of dynamic MRI (instead of static series of 3D CT done so far) to explore 3D carpal dynamics to detect kinematic wrist abnormalities in diagnosis/staging/management, to study carpal motion in health/disease, and to evaluate results after surgery Collaborators: Catherine N. Petchprapa, MD, NYU Langone Musculoskeletal Imaging & Radiology, and Riccardo Lattanzi, NYU Langone Radiology. Challenges for image analysis include segmentation of wrist bones from a longitudinal series of relatively low resolution MRI with anisotropic voxels, consistent segmentation of individual bones across the time series, and joint spatiotemporal modeling of extracted bones as a multi-object complex.		3D segmentation of individual bones was solved via level-set segmentation within itkSNAP. Preliminary tests with Slicer GrowCut were not satisfactory due to highly non-isotropic voxels, but more tests will be necessary to explore new advanced features within "Segment Editor".

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-The goal of this project is to analyze wrist kinematics from a dynamic MRI sequence. Challenges include segmentation of wrist bones from relatively low resolution MRI with anisotropic voxels, and joint spatiotemporal modeling of extracted bones as a multi-object complex.
+* The clinical goal of this project is the use of dynamic MRI (instead of static series of 3D CT done so far) to explore 3D carpal dynamics to detect kinematic wrist abnormalities in diagnosis/staging/management, to study carpal motion in health/disease, and to evaluate results after surgery
+* Collaborators:  Catherine N. Petchprapa, MD, NYU Langone Musculoskeletal Imaging & Radiology, and Riccardo Lattanzi, NYU Langone Radiology.
+* Challenges for image analysis include segmentation of wrist bones from a longitudinal series of relatively low resolution MRI with anisotropic voxels, consistent segmentation of individual bones across the time series, and joint spatiotemporal modeling of extracted bones as a multi-object complex.
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