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The analysis of MR images is evolving from qualitative to quantitative. More and more, the question asked by clinicians is how much and where, rather than a simple statement on the presence or absence of abnormalities. The authors present a study in which the results obtained with a semiautomatic, multispectral segmentation technique are quantitatively(More)
This paper presents a comparison study between 10 automatic and six interactive methods for liver segmentation from contrast-enhanced CT images. It is based on results from the "MICCAI 2007 Grand Challenge" workshop, where 16 teams evaluated their algorithms on a common database. A collection of 20 clinical images with reference segmentations was provided(More)
Nonrigid registration of medical images is important for a number of applications such as the creation of population averages, atlas-based segmentation, or geometric correction of functional magnetic resonance imaging (fMRI) images to name a few. In recent years, a number of methods have been proposed to solve this problem, one class of which involves(More)
A number of supervised and unsupervised pattern recognition techniques have been proposed in recent years for the segmentation and the quantitative analysis of MR images. However, the efficacy of these techniques is affected by acquisition artifacts such as inter-slice, intra-slice, and inter-patient intensity variations. Here a new approach to the(More)
Biomechanical models that describe soft tissue deformation provide a relatively inexpensive way to correct registration errors in image-guided neurosurgical systems caused by nonrigid brain shift. Quantifying the factors that cause this deformation to sufficient precision is a challenging task. To circumvent this difficulty, atlas-based methods have been(More)
OBJECTIVE Liver surgery is difficult because of limited external landmarks, significant vascularity, and inexact definition of intra-hepatic anatomy. Intra-operative ultrasound (IOUS) has been widely used in an attempt to overcome these difficulties, but is limited by its two-dimensional nature, inter-user variability, and image obliteration with ablative(More)
Compensating for intraoperative brain shift using computational models has shown promising results. Since computational time is an important factor during neurosurgery, a priori knowledge of the possible sources of deformation can increase the accuracy of model-updated image-guided systems. In this paper, a strategy to compensate for distributed loading(More)
The authors present a weighted geometrical feature (WGF) registration algorithm. Its efficacy is demonstrated by combining points and a surface. The technique is an extension of Besl and McKay's (1992) iterative closest point (ICP) algorithm. The authors use the WGF algorithm to register X-ray computed tomography (CT) and T2-weighted magnetic resonance (MR)(More)
A successful surface-based image-to-physical space registration in image-guided liver surgery (IGLS) is critical to provide reliable guidance information to surgeons and pertinent surface displacement data for use in deformation correction algorithms. The current protocol used to perform the image-to-physical space registration involves an initial pose(More)
HYPOTHESIS Using automated methods, vital anatomy of the middle ear can be identified in computed tomographic (CT) scans and used to create 3-dimensional (3D) renderings. BACKGROUND Although difficult to master, clinicians compile 2D data from CT scans to envision 3D anatomy. Computer programs exist that can render 3D surfaces but are limited in that ear(More)