Non-rigid registration of the liver in consecutive CT studies for assessment of tumor response to radiofrequency ablation.
This paper introduces a non-rigid registration approach for tracking tumor response to radiofrequency ablation (RFA) across consecutive imaging studies. The method described here exploits the combined power of global and local alignment of pre- and post-treatment CT liver images for a given patient. The distinguishing characteristics of the system is that it can infer volumetric deformation based upon surface displacements using a linearly elastic finite element model (FEM). This technique may provide valuable information that could be beneficial in a range of surgical interventions as well as for the purposes of monitoring tissue response and therapy planning.
Niculescu
Gabriela
G
Department of Biomedical Engineering, Rutgers University and the Center for Biomedical Imaging & Informatics, UMDNJ-Robert Wood Johnson Medical School, Piscataway, NJ 08854, USA. gnicules@eden.rutgers.edu
Foran
David J
DJ
Nosher
John
J
D000465:Algorithms; D001185:Artificial Intelligence; D017115:Catheter Ablation / Q000379:methods*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D008113:Liver Neoplasms / Q000000981:diagnostic imaging* / Q000601:surgery*; D010363:Pattern Recognition, Automated / Q000379:methods; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D025321:Surgery, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*; D016896:Treatment Outcome