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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

Simultaneous quantification of cell motility and protein-membrane-association using active contours.

TL;DR: A new method for the quantification of dynamic changes in fluorescence intensities at the cell membrane of moving cells, based on an active contour method for cell-edge detection, which allows tracking of changes in cell shape and position is presented.
Book ChapterDOI

Medical Image Segmentation: A Brief Survey

TL;DR: Most popular medical image segmentation techniques are overviews and their capabilities, and basic advantages and limitations are discussed.
Journal ArticleDOI

Automated microscopic image analysis for leukocytes identification: A survey

TL;DR: In this review, this work has categorized, evaluated, and discussed recently developed methods for leukocyte identification, and found their constraints.
Journal ArticleDOI

Three validation metrics for automated probabilistic image segmentation of brain tumours

TL;DR: The segmentation accuracy based on three two‐sample validation metrics against the estimated composite latent gold standard, which was derived from several experts' manual segmentations by an EM algorithm, yielded satisfactory accuracy with varied optimal thresholds.
Journal ArticleDOI

Parallel implementation for 3D medical volume fuzzy segmentation

TL;DR: A hybrid parallel implementation of FCM for extracting volume objects from medical files is proposed and it is concluded that the parallel implementation is 5X faster than the sequential version of the same operation.
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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