M3VR—A multi-stage, multi-resolution, and multi-volumes-of-interest volume registration method applied to 3D endovaginal ultrasound

Abstract

Heterogeneity of echo-texture and lack of sharply delineated tissue boundaries in diagnostic ultrasound images make three-dimensional (3D) registration challenging, especially when the volumes to be registered are considerably different due to local changes. We implemented a novel computational method that optimally registers volumetric ultrasound image data containing significant and local anatomical differences. It is A Multi-stage, Multi-resolution, and Multi-volumes-of-interest Volume Registration Method. A single region registration is optimized first for a close initial alignment to avoid convergence to a locally optimal solution. Multiple sub-volumes of interest can then be selected as target alignment regions to achieve confident consistency across the volume. Finally, a multi-resolution rigid registration is performed on these sub-volumes associated with different weights in the cost function. We applied the method on 3D endovaginal ultrasound image data acquired from patients during biopsy procedure of the pelvic floor muscle. Systematic assessment of our proposed method through cross validation demonstrated its accuracy and robustness. The algorithm can also be applied on medical imaging data of other modalities for which the traditional rigid registration methods would fail.

GMCNet: A Generative Multi-Resolution Framework for Cardiac Registration

“…Deformable image registration could also be performed in multiple stages and multiple resolutions to speed up and reduce sensitivity to local optima and image folding [29], [30]. Multi-stage approaches commonly start with affine or other linear registrations followed by coarse-to-fine deformable image registration [24], [31], [32].…”