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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Journal ArticleDOI
Conditioning of deep-learning surrogate models to image data with application to reservoir characterization
TL;DR: From comparisons with conventional workflows based entirely on high-fidelity simulation models, it is concluded that the proposed surrogate-supported hybrid workflow is able to deliver results with an accuracy equal to or better than the conventional workflow, and at significantly lower cost.
Journal ArticleDOI
Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images
TL;DR: An efficient ATFL segmentation framework is developed that is computationally more efficient and more accurate with lowest rate of coefficient of variation (less than 5 %) that indicates the highest clinical significance of this research in the assessment of ATFL injuries.
Dissertation
Realistic Analysis for Algorithmic Problems on Geographical Data
TL;DR: In this article, it was shown that computing the Frechet distance exactly is an NP-hard problem and that the complexity of the Voronoi diagram is additively linear in the size of the terrain and the number of sites.
Proceedings ArticleDOI
Method for fast and accurate segmentation processing from prior shape: application to femoral head segmentation on x-ray images
TL;DR: In this paper, a prior shape segmentation method is proposed to create a constant width ribbon-like zone that runs along the boundary to be extracted, and the image data corresponding to that zone is transformed into a rectangular image subspace where the boundary is roughly straightened.
Journal ArticleDOI
Multiparametric Iterative Self-Organizing Data Analysis of Ischemic Lesions Using Pre- or Post-Gd T1 MRI
Hamid Soltanian-Zadeh,Hassan Bagher-Ebadian,James R. Ewing,Panayiotis D. Mitsias,Alissa Kapke,Mei Lu,Quan Jiang,Suresh C. Patel,Michael Chopp +8 more
TL;DR: This study shows that the multiparametric ISODATA approach consistently identifies and characterizes the core of the ischemic lesion and confirms that the multi-parametric ISodATA MRI characterizes tissue damage and recovery in stroke.
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.
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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.