scispace - formally typeset
Journal ArticleDOI

Design and construction of a realistic digital brain phantom

Reads0
Chats0
TLDR
The authors present a realistic, high-resolution, digital, volumetric phantom of the human brain, which can be used to simulate tomographic images of the head and is the ideal tool to test intermodality registration algorithms.
Abstract
After conception and implementation of any new medical image processing algorithm, validation is an important step to ensure that the procedure fulfils all requirements set forth at the initial design stage. Although the algorithm must be evaluated on real data, a comprehensive validation requires the additional use of simulated data since it is impossible to establish ground truth with in vivo data. Experiments with simulated data permit controlled evaluation over a wide range of conditions (e.g., different levels of noise, contrast, intensity artefacts, or geometric distortion). Such considerations have become increasingly important with the rapid growth of neuroimaging, i.e., computational analysis of brain structure and function using brain scanning methods such as positron emission tomography and magnetic resonance imaging. Since simple objects such as ellipsoids or parallelepipedes do not reflect the complexity of natural brain anatomy, the authors present the design and creation of a realistic, high-resolution, digital, volumetric phantom of the human brain. This three-dimensional digital brain phantom is made up of ten volumetric data sets that define the spatial distribution for different tissues (e.g., grey matter, white matter, muscle, skin, etc.), where voxel intensity is proportional to the fraction of tissue within the voxel. The digital brain phantom can be used to simulate tomographic images of the head. Since the contribution of each tissue type to each voxel in the brain phantom is known, it can be used as the gold standard to test analysis algorithms such as classification procedures which seek to identify the tissue "type" of each image voxel. Furthermore, since the same anatomical phantom may be used to drive simulators for different modalities, it is the ideal tool to test intermodality registration algorithms. The brain phantom and simulated MR images have been made publicly available on the Internet (http://www.bic.mni.mcgill.ca/brainweb).

read more

Citations
More filters
Journal Article

Multimodal Brain Warping Using the Demons Algorithm and Adaptative Intensity Corrections

TL;DR: It is argued that the intensity modeling may be more appropriate than mutual information (MI) in the context of evaluating high-dimensional deformations, as it puts more constraints on the parameters to be estimated and thus permits a better search of the parameter space.
Journal ArticleDOI

Accelerated Regularized Estimation of MR Coil Sensitivities Using Augmented Lagrangian Methods

TL;DR: An iterative algorithm based on variable splitting and the augmented Lagrangian method that estimates the coil sensitivity profile by minimizing a quadratic cost function and a faster variant of this algorithm using intermediate updating of the associated Lagrange multipliers is presented.
Proceedings ArticleDOI

A work-efficient GPU algorithm for level set segmentation

TL;DR: This work presents a novel GPU level set segmentation algorithm that is both work-efficient and step-efficient, and employs a novel parallel method for removing duplicate elements from unsorted data streams in a constant number of steps.
Reference EntryDOI

Journal De La Société Française De Statistique

TL;DR: The history of the Journal of the Statistical Society of Paris (1860-1998) can be found in this paper, where the journal was referred to as the journal of the French Statistical Society.
Journal ArticleDOI

Accuracy assessment of global and local atrophy measurement techniques with realistic simulated longitudinal Alzheimer's disease images

TL;DR: A technique in which atrophy is realistically simulated in different tissue compartments or neuroanatomical structures with a phenomenological model is presented and the accuracy of several well-known computational anatomy methods which provide global or local estimates of longitudinal atrophy in brain structures using MR images is assessed.
References
More filters
Book

Pattern Recognition with Fuzzy Objective Function Algorithms

TL;DR: Books, as a source that may involve the facts, opinion, literature, religion, and many others are the great friends to join with, becomes what you need to get.
Book

Co-planar stereotaxic atlas of the human brain : 3-dimensional proportional system : an approach to cerebral imaging

TL;DR: Direct and Indirect Radiologic Localization Reference System: Basal Brain Line CA-CP Cerebral Structures in Three-Dimensional Space Practical Examples for the Use of the Atlas in Neuroradiologic Examinations Three- Dimensional Atlas of a Human Brain Nomenclature-Abbreviations Anatomic Index Conclusions.
Journal ArticleDOI

A nonparametric method for automatic correction of intensity nonuniformity in MRI data

TL;DR: A novel approach to correcting for intensity nonuniformity in magnetic resonance (MR) data is described that achieves high performance without requiring a model of the tissue classes present, and is applied at an early stage in an automated data analysis, before a tissue model is available.
Journal ArticleDOI

Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space

TL;DR: A fully automatic registration method to map volumetric data into stereotaxic space that yields results comparable with those of manually based techniques and therefore does not suffer the drawbacks involved in user intervention.
Book

Introduction to artificial neural systems

TL;DR: Jacek M. Zurada is a Professor with the Electrical and Computer Engineering Department at the University of Louisville, Kentucky and has published over 350 journal and conference papers in the areas of neural networks, computational intelligence, data mining, image processing and VLSI circuits.
Related Papers (5)