Flexible Reconstruction and Correction of Unpredictable Motion from Stacks of 2D Images

Abstract

Abstract. We present a method to correct motion in fetal in-utero scan sequences. The proposed approach avoids previously necessary manual segmentation of a region of interest. We solve the problem of non-rigid motion by splitting motion corrupted slices into overlapping patches of finite size. In these patches the assumption of rigid motion approximately holds and they can thus be used to perform a slice-to-volumebased (SVR) reconstruction during which their consistency with the other patches is learned. The learned information is used to reject patches that are not conform with the motion corrected reconstruction in their local areas. We evaluate rectangular and evenly distributed patches for the reconstruction as well as patches that have been derived from superpixels. Both approaches achieve on 29 subjects aged between 22-37 weeks a sufficient reconstruction quality and facilitate following 3D segmentation of fetal organs and the placenta.

Fast Fully Automatic Segmentation of the Human Placenta from Motion Corrupted MRI

“…A native plane (a) cannot represent all structures of the placenta at once. Therefore, we use our segmentation method (b), correct the motion in this area using [3], project the placenta mask into the the resulting isotropically resolved volume (c), extract the mean curvature flow skeleton [10] (black lines in (d)), use the resulting points to support a curved surface plane (e) and visualize this plane with curved planar reformation [5] (f). The plane in (f) covers only relevant areas, hence gray value mapping can be adjusted automatically to emphasis placental structures.…”

“…It is also capable of segmenting the placenta from dissimilar data by achieving segmentation accuracy of 66.89% for a cohort mixed with cases of intrauterine fetal growth restriction . A comparisons between the 3D reconstructed placenta using superpixel-based PVR reconstructions [3] with initial superpixel size 20x20 pixels and a baseline using directly 2D slices from the input stacks for multi-planar examination. (stacks with high motion artifacts were excluded) from different scanners.…”

“…Although this tissue classification approach is capable of segmenting the placenta robustly, the segmentation is still subject to inter-slice motion artifacts. Placenta segmentation recovery: To tackle these motion artifacts caused by fetal and maternal movements we combine our segmentation framework with flexible motion compensation algorithm based on patch-to-volume registration (PVR) [3]. This technique requires multiple orthogonal stacks of 2D slices to provide a better reconstruction quality.…”

Learning clinically useful information from images: Past, present and future

“…Until recently, these methods could not be applied outside the fetal brain because of the assumption of rigid motion in the 2D to 3D registration step of slice-to-volume registration (SVR) methods. To solve this problem we have developed a patch-to-volume registration (PVR) approach, which employs a flexible subdivision of the input space into overlapping and partly rigid image patches [Kainz et al (2015a)]. This way the motion compensation problem is solved for each patch independently without requiring an a-priori defined region of inter- est.…”

Placenta Maps: In Utero Placental Health Assessment of the Human Fetus

“…Predictable motion, like respiration, can be corrected with image navigator techniques or special MRI sequences [22]. But it is only possible to account for bowel and erratic fetal movements after image acquisition using heavy oversampling of the input space, slice-to-volume registration, and super-resolution techniques [23], [24].…”