Thoracic CT-PET registration using a 3D breathing model.
In the context of thoracic CT-PET volume registration, we present a novel method to incorporate a breathing model in a non-linear registration procedure, guaranteeing physiologically plausible deformations. The approach also accounts for the rigid motions of lung tumors during breathing. We performed a set of registration experiments on one healthy and four pathological data sets. Initial results demonstrate the interest of this method to significantly improve the accuracy of multimodal volume registration for diagnosis and radiotherapy applications.
Moreno
Antonio
A
Ecole Nationale Supérieure des Télécommunications (GET - Télécom Paris), CNRS UMR 5141 LTCI - Signal and Image Processing Department, Paris, France.
Chambon
Sylvie
S
Santhanam
Anand P
AP
Brocardo
Roberta
R
Kupelian
Patrick
P
Rolland
Jannick P
JP
Angelini
Elsa
E
Bloch
Isabelle
I
D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008175:Lung Neoplasms / Q000175:diagnosis*; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D049268:Positron-Emission Tomography / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods; D015203:Reproducibility of Results; D015656:Respiratory Mechanics; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D013909:Thorax / Q000000981:diagnostic imaging; D014057:Tomography, X-Ray Computed / Q000379:methods*