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Rigid point-based registration technique is widely used in many aspects of image-guided surgery (IGS). Estimating target registration error (TRE) statistics considering a coordinate reference frame (CRF) is of essential value for applications such as optical tracking and image registration. In this paper, we extend the TRE estimation algorithm relative to a CRF to general fiducial localization error...
Deformable registration based multi-atlas segmentation has been successfully applied in a broad range of anatomy segmentation applications. However, the excellent performance comes with a high computational burden due to the requirement for deformable image registration and voxel-wise label fusion. To address this problem, we conduct an experimental study to investigate trade-off between computational...
Functional optical imaging (OI) of intrinsic signals (like blood oxygenation coupled reflection changes) and of extrinsic properties of voltage sensitive probes (like voltage-sensitive dyes (VSD)) forms a group of invasive neuroimaging techniques, that possess up to date the highest temporal and spatial resolution on a meso- to macroscopic scale.
Quantifying T cells inside tumorous tissue can help identifying immune profiles in order to improve prognosis and possibly develop immunotherapy. However, to identify T cells and cancerous cells in two consecutive staining slides is challenging: the tissue preparation introduces the problem of alignment on large size images with poor visual common information. This work presents a framework for aligning...
High-throughput serial histology imaging provides a new avenue for the routine study of micro-anatomical structures in a 3D space. However, the emergence of serial whole slide imaging poses a new registration challenge, as the gigapixel image size precludes the direct application of conventional registration techniques. In this paper, we develop a three-stage registration with multi-resolution mapping...
The evolutionary success of ants and other social insects is considered to be intrinsically linked to division of labor and emergent collective intelligence. The role of the brains of individual ants in generating these processes, however, is poorly understood. One genus of ant of special interest is Pheidole, which includes more than a thousand species, most of which are dimorphic, i.e. their colonies...
This paper addresses a dense voxel-wise correspondence of cone-beam computed tomography (CBCT) images towards a non-rigid registration and treatments evaluation in clinical orthodontics. An unsupervised clustering randomized forest is employed to establish voxel-wise correspondence in a reduced subset of the original volume image. A geodesic coordinate is introduced to avoid the structural ambiguities...
Accurate registration plays a critical role in group-wise functional Magnetic Resonance Imaging (fMRI) image analysis, as spatial correspondence among different brain images is a prerequisite for inferring meaningful patterns. However, the problem is challenging and remains open, and more effort should be made to advance the state-of-the-art image registration methods for fMRI images. Inspired by...
This paper addresses the estimation of pairwise supervoxel correspondences toward automatic semi-dense medical image registration. Supervoxel matching is performed through random forests (RF) with supervoxel indexes as label entities to predict matching areas in another target image. Ensuring accurate supervoxel boundary adherence requires a fine supervoxel decomposition which highly increases learning...
Cortical folds encode crucial information of brain development, cytoarchitecture and function. It is widely accepted that common anatomy is preserved across individuals within species, while huge variation still hamper establishing fine-grained anatomical correspondences and predicting the locations of a specific anatomical pattern via conventional image registration methods, especially for complex...
We introduce a deep encoder-decoder architecture for image deformation prediction from multimodal images. Specifically, we design an image-patch-based deep network that jointly (i) learns an image similarity measure and (ii) the relationship between image patches and deformation parameters. While our method can be applied to general image registration formulations, we focus on the Large Deformation...
Diffeomorphic image registration algorithms are widely used in medical imaging, and require optimization of a high-dimensional nonlinear objective function. The function being optimized has many characteristics that are relevant for optimization but are typically not well understood. Due to that complexity, most authors have used a simple gradient descent, but it is not often discussed how step sizes...
In the field of medical imaging, atlases are generally used for computer-aided anatomical and functional parcellation of a brain, and for distinguishing which tissue is normal and which is pathologic. The purpose of this paper is to create a set of human brain atlas probability maps, which would be publicly available for clinical and research community and could be applied to computer tomography (CT)...
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