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SU‐E‐J‐85: Landmark‐Driven Interactive Deformable Image Registration
Author(s) -
Shushari,
Pieper S,
Sharp G
Publication year - 2013
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4814297
Subject(s) - landmark , image registration , computer vision , artificial intelligence , computer science , matching (statistics) , position (finance) , point set registration , similarity measure , point (geometry) , image (mathematics) , mathematics , statistics , geometry , finance , economics
Purpose: To build a framework for deformable B‐spline image registration with user controlled accuracy by using the positions of point landmarks as guidance. Methods: Manually identified point landmarks are placed on the reference image and their corresponding locations on the test image. An intensity‐based similarity measure is optimized under the constraint of minimizing the distance between the corresponding landmarks. After the Result of registration is visually inspected, the positions of the landmarks may be manually adjusted to improve matching accuracy. Each landmark adjustment operation triggers a re‐optimization routine, which can be repeated until the desired accuracy is reached. Results: We have tested the method on medical use cases to register CT images of the upper body, common in radiotherapy of head and neck cancer. The registration of these images compensates for position error, including pitch and yaw of the head, and flexion of the spine. Deformable registration of these images is very challenging when there is a large spatial shift of the head position. Placing landmarks on a single cross‐section and running optimization one or two times leads to a satisfactory Result . Conclusion: We have developed a practical method of interactive, intuitive correction of deformable registration of medical images. The method integrates both intensity and landmark matching. Our results prove the feasibility of the method and demonstrate potential of the tool for clinical applications.