Journal ArticleDOI
Current methods in medical image segmentation.
TLDR
A critical appraisal of the current status of semi-automated and automated methods for the segmentation of anatomical medical images is presented, with an emphasis on the advantages and disadvantages of these methods for medical imaging applications.Abstract:
▪ Abstract Image segmentation plays a crucial role in many medical-imaging applications, by automating or facilitating the delineation of anatomical structures and other regions of interest. We present a critical appraisal of the current status of semiautomated and automated methods for the segmentation of anatomical medical images. Terminology and important issues in image segmentation are first presented. Current segmentation approaches are then reviewed with an emphasis on the advantages and disadvantages of these methods for medical imaging applications. We conclude with a discussion on the future of image segmentation methods in biomedical research.read more
Citations
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Journal ArticleDOI
A novel region-based level set method initialized with mean shift clustering for automated medical image segmentation
TL;DR: In this study, a novel region-based level set method utilizing both global and local image information complementarily is proposed, which confirms the efficiency and accuracy of the proposed method for medical image segmentation.
Proceedings ArticleDOI
Classification of tumors and it stages in brain MRI using support vector machine and artificial neural network
TL;DR: Support Vector Machine and Artificial Neural Network based tumor and its stages classification in brain MRI images is presented in this research work and the accuracy of classifying normal and tumor brain this proposed method is better than other methods.
Proceedings ArticleDOI
Free software tools for atlas-based volumetric neuroimage analysis
TL;DR: New and freely available software tools for measuring volumes in subregions of the brain based on the Talairach-Tournoux atlas are described and released as plug-ins for MIPAV, a freely available and user-friendly image analysis software package developed by the National Institutes of Health.
Book ChapterDOI
Effective Segmentation for Dental X-Ray Images Using Texture-Based Fuzzy Inference System
Y. H. Lai,P. L. Lin +1 more
TL;DR: This paper proposes a novel scheme to automatically segment teeth by using texture characteristics instead of primitive intensity or edge used in previous researches, and shows that the proposed method indeed outperforms the methods using directintensity or edge in segmenting complete teeth from X-ray dental images.
Journal ArticleDOI
Decomposing the Hounsfield unit: probabilistic segmentation of brain tissue in computed tomography.
TL;DR: Automated tissue segmentation of cranial CT images using highly refined tissue probability maps derived from high resolution MR images is feasible and potential applications include automated quantification of WM in leukoaraiosis, CSF in hydrocephalic patients, GM in neurodegeneration and ischemia and perfusion maps with separate assessment of GM and WM.
References
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Book
Fuzzy sets
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Book
Neural Networks: A Comprehensive Foundation
TL;DR: Thorough, well-organized, and completely up to date, this book examines all the important aspects of this emerging technology, including the learning process, back-propagation learning, radial-basis function networks, self-organizing systems, modular networks, temporal processing and neurodynamics, and VLSI implementation of neural networks.
Journal ArticleDOI
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
Stuart Geman,Donald Geman +1 more
TL;DR: The analogy between images and statistical mechanics systems is made and the analogous operation under the posterior distribution yields the maximum a posteriori (MAP) estimate of the image given the degraded observations, creating a highly parallel ``relaxation'' algorithm for MAP estimation.
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.