US 11,940,578 B2
Super resolution in positron emission tomography imaging using ultrafast ultrasound imaging
Bertrand Tavitian, Paris (FR); Mickaël Tanter, Paris (FR); Mailyn Perez-Liva, Paris (FR); Joaquin Lopez Herraiz, Madrid (ES); and Jean Provost, Montreal (CA)
Assigned to INSERM (INSTITUT NATIONAL DE LA SANTÉ ET DE LA RECHERCHE MÉDICALE), Paris (FR); UNIVERSITÉ DE PARIS, Paris (FR); CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE—CNRS, Paris (FR); and ECOLE SUPERIEURE DE PHYSIQUE ET DE CHIMIE INDUSTRIELLES DE LA VILLE DE PARIS, Paris (FR)
Filed by INSERM (Institut National de la Santé et de la Recherche Médicale), Paris (FR); Université de Paris, Paris (FR); Centre National de la Recherche Scientifique (CNRS), Paris (FR); and Ecole Supérieure de Physique et de Chimie Industrielles de la Ville de Paris, Paris (FR)
Filed on Jan. 28, 2021, as Appl. No. 17/160,866.
Claims priority of application No. 20154857 (EP), filed on Jan. 31, 2020.
Prior Publication US 2021/0239863 A1, Aug. 5, 2021
Int. Cl. G01T 1/29 (2006.01); A61B 6/00 (2006.01)
CPC G01T 1/2985 (2013.01) [A61B 6/5229 (2013.01); A61B 6/5235 (2013.01)] 20 Claims
OG exemplary drawing
 
1. An imaging method including:
a) acquiring N successive positron emission tomography (PET) low resolution images Γi and simultaneously, N successive Ultrafast Ultrasound Imaging (UUI) images Ui of a moving object;
b) determining from each UUI image Ui, the motion vector fields Mi that corresponds to the spatio-temporal geometrical transformation of the motion of the object;
c) obtaining a final estimated high resolution image H of the object by iterative determination of a high resolution image Hn+1 obtained by applying several correction iterations to a current estimated high resolution image Hn, n being the number of iterations, starting from an initial estimated high resolution image H1 of the object, each correction iteration including at least:
i) warping said estimated high resolution image Hn using the motion vector fields Mi to determine a set of low resolution reference images Lni;
ii) determining a differential image Di by difference between each PET image Γi and the corresponding low resolution reference image Lni;
iii) warping back said differential images Di using the motion vector fields Mi and averaging the N warped back differential images to obtain a high resolution differential image;
iv) determining the high resolution image Hn+1 by correcting said high resolution image Hn using said high resolution differential image;
d) applying the motion vector fields Mi of each UUI image Ui to said final high resolution image H.