Deformable Mosaicing for Whole-Body MRI

Abstract

Abstract. Whole-body magnetic resonance imaging is an emerging application gaining vast clinical interest during the last years. Although recent technological advances shortened the longish acquisition time, this is still the limiting factor avoiding its wide-spread clinical usage. The acquisition of images with large field-of-view helps to relieve this drawback, but leads to significantly distorted images. Therefore, we propose a deformable mosaicing approach, based on the simultaneous registration to linear weighted averages, to correct for distortions in the overlapping area. This method produces good results on in-vivo data and has the advantage that a seamless integration into the clinical workflow is possible.

Imaging and shape analysis of the moving human fetal brain in-utero

“…Image mosaicing [9] seeks to merge sub-images into a single image, to provide either an enlarged field of view [10] by increasing the spatial extent of the data, or an improved resolution [11] by increasing the spatial frequency extent of the data. It has been used in MRI [12] to extend the field of view of an image. In the context of fetal MRI.…”

MRI Composing for Whole Body Imaging

“…In order to introduce our approach of deformable composing recently proposed [3], we define the two volumes to be stitched as I 1 :…”

Automated extraction and labelling of the arterial tree from whole-body MRA data

“…This can be explained by the relative novelty of the field itself. Several published methods considered either intensity normalization of multiple acquired image stacks (Jäger and Hornegger, 2009), or stitching of entire 3D volumes with simultaneous correction of geometrical distortions (Wachinger et al, 2008). A large array of the bias correction methods for MR data that has been published during past years (Pham and Prince, 1999;Sled et al, 1998;Van Leemput et al, 1999;Wells et al, 1996) was so far primarily developed and applied to neurological (brain) images, and feasibility of application of these methods to WB-MR data remains an open question.…”