  A method was proposed for the point cloud-based registration and image fusion
between cardiac single photon emission computed tomography (SPECT) myocardial
perfusion images (MPI) and cardiac computed tomography angiograms (CTA).
Firstly, the left ventricle (LV) epicardial regions (LVERs) in SPECT and CTA
images were segmented by using different U-Net neural networks trained to
generate the point clouds of the LV epicardial contours (LVECs). Secondly,
according to the characteristics of cardiac anatomy, the special points of
anterior and posterior interventricular grooves (APIGs) were manually marked in
both SPECT and CTA image volumes. Thirdly, we developed an in-house program for
coarsely registering the special points of APIGs to ensure a correct cardiac
orientation alignment between SPECT and CTA images. Fourthly, we employed ICP,
SICP or CPD algorithm to achieve a fine registration for the point clouds
(together with the special points of APIGs) of the LV epicardial surfaces
(LVERs) in SPECT and CTA images. Finally, the image fusion between SPECT and
CTA was realized after the fine registration. The experimental results showed
that the cardiac orientation was aligned well and the mean distance error of
the optimal registration method (CPD with affine transform) was consistently
less than 3 mm. The proposed method could effectively fuse the structures from
cardiac CTA and SPECT functional images, and demonstrated a potential in
assisting in accurate diagnosis of cardiac diseases by combining complementary
advantages of the two imaging modalities.
