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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

Computer-aided cephalometric landmark annotation for CBCT data

TL;DR: A computer-aided landmark annotation approach that estimates the three-dimensional (3D) positions of 21 selected landmarks and was acceptable for most of landmarks and comparable with other available methods is proposed.
Journal ArticleDOI

Stepping into the third dimension.

TL;DR: An overview of the principles and practices of 3D visualization of multichannel microscopic data is provided and a new software package for volume visualization and data analysis is described, called ImageSurfer, which is designed with fluorescent microscopy in mind and effective for other types of data.
Journal ArticleDOI

Fast and globally convex multiphase active contours for brain MRI segmentation

TL;DR: Experimental results indicate that the proposed approach provides consistently better accuracy than other related multiphase active contour algorithms using four different error metrics even under severe noise, intensity inhomogeneities, and partial volume effects in MRI imagery.
Journal ArticleDOI

Replica inference approach to unsupervised multiscale image segmentation.

TL;DR: This approach applies a replica-inference-based Potts model method to unsupervised image segmentation on multiple scales and is fast and shown to be at least as accurate as the best algorithms to date and to be especially suited to the detection of camouflaged images.

Detecting Hand Bone Fractures in X-Ray Images

TL;DR: For a first attempt to tackle such a difficult problem, the proposed system to automatically detect fractures in hand bones using x-ray images performed incredibly good with a 91.8% accuracy.
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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