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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

Modelling cardiac calcium sparks in a three-dimensional reconstruction of a calcium release unit

TL;DR: A detailed computational model of a cardiac Ca2+ spark is developed based on a three dimensional reconstruction of electron tomograms that predicts near total junctionalCa2+ depletion after the spark, while regional Ca2- reserve is preserved.
Patent

Tracking system using field mapping

Doron Harlev, +1 more
TL;DR: In this paper, a method for securing multiple sets of current injecting electrodes to an organ in a patient's body in order to generate a field in the organ, in response to current flow caused by the multiple sets, is described.

Segmentation of the Brain from MR Images

Jenny Caesar
TL;DR: This thesis project consists of finding a method to extract brain tissues from T1-weighted MR images of the head using the expectation-maximization algorithm and it corrects for intensity inhomogeneities.
Journal ArticleDOI

Oriented Active Shape Models

TL;DR: A novel strategy called oriented active shape models (OASM) is presented in an attempt to overcome the following five limitations of ASM: lower delineation accuracy, the requirement of a large number of landmarks, sensitivity to search range, 4) sensitivity to initialization, and 5) inability to fully exploit the specific information present in the given image to be segmented.
Journal ArticleDOI

Automatic Human Brain Tumor Detection in MRI Image Using Template-Based K Means and Improved Fuzzy C Means Clustering Algorithm

TL;DR: Simulation results show that the proposed algorithm achieves better detection of abnormal and normal tissues in the human brain under small detachment of gray-level intensity and detects human brain tumors within a very short time—in seconds compared to minutes with other algorithms.
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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