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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.

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Citations
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Journal ArticleDOI

Identifying Regions of Interest in Medical Images Using Self-Organizing Maps

TL;DR: A two-stage SOM approach is devised that can be used to precisely identify the dominant colors of a medical image and then segment it into several small regions, and radiologists can usually identify one or more ROIs within amedical image.
Book ChapterDOI

Piecewise Rigid Multimodal Spine Registration

TL;DR: An efficient and robust vertebra segmentation algorithm for CT data that proved reliable even for cases with damaged vertebrae or missing intervertebral discs is presented.
Patent

System and method for using learned discriminative models to segment three dimensional colon image data

TL;DR: In this article, a system and method for using learned discriminative models to segment a border of an anatomical structure in a three dimensional (3D) image is disclosed, and an initial 3D segmentation is obtained.
Journal ArticleDOI

Voyaging into the third dimension: A perspective on virtual methods and their application to studies of juvenile sex estimation and the ontogeny of sexual dimorphism.

TL;DR: The suitability and potential of virtual methods for juvenile sex estimation are evaluated with the aims of identifying the benefits and challenges associated with virtual data and quantitative analysis of 3D models, and pathways that may lead to practical improvements for sexing juveniles.
Journal ArticleDOI

DOST: a distributed object segmentation tool

TL;DR: The visual and objective evaluation and comparison with the existing techniques show that the proposed tool can deliver optimal performance when applied to tough object segmentation tasks.
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

Simon Haykin
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

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.
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