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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Book ChapterDOI
Data Analysis and Classification
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Journal ArticleDOI
Oversegmentation reduction in watershed-based grey-level image segmentation
TL;DR: In this paper, the watershed transformation is used to partition the image into homogeneous regions, and then the successive assignment of the regions to either the foreground or the background is performed.
Journal ArticleDOI
Robust Active Contour Model Using Patch-Based Signed Pressure Force and Optimized Fractional-Order Edge
TL;DR: Wang et al. as mentioned in this paper proposed an active contour model (ACM) consisting of a local fitting term, an edge-based term and an external force term for image segmentation.
Proceedings ArticleDOI
Acceleration of Medical Image Registration Using Graphics Process Units in Computing Normalized Mutual Information
Wei-Hung Cheng,Cheng-Chang Lu +1 more
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Automatic Spine Segmentation using Convolutional Neural Network via Redundant Generation of Class Labels for 3D Spine Modeling.
TL;DR: A fully automatic approach for spine segmentation from CT based on a hybrid method that combines the convolutional neural network (CNN) and fully Convolutional network (FCN) and utilizes class redundancy as a soft constraint to greatly improve the segmentation results.
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.