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
Automated segmentation of tissue structures in optical coherence tomography data
TL;DR: Two methods for the automated segmentation of arbitrary structures in OCT images are proposed, performing a seeded region growing and applying a model-based analysis of OCT A-scans for the seed's acquisition, which avoids any user-intervention dependency.
Journal ArticleDOI
Review of Breast Cancer Pathologigcal Image Processing
TL;DR: In this paper, a breast cancer recognition method based on image processing is systematically expounded from four aspects: breast cancer detection, image segmentation, image registration, and image fusion.
Journal ArticleDOI
GA-based multiresolution fusion of segmented brain images using PD-, T1- and T2-weighted MR modalities
TL;DR: Experimental results show that Gibbs- and ICM-based segmentation approaches related to Markov random field perform over the fuzzy C-mean and which are being used prior to GA-based fusion process for MR T1, MR T2 and MR PD images of section of human brain.
Proceedings ArticleDOI
Segmentation of Medical Images with Regional Inhomogeneities
TL;DR: The results show that the proposed model can be effectively utilized for the delineation of abnormal tissue findings, and in presence of regional inhomogeneities it can be more accurate compared with the ACWE model.
High-throughput hyperdimensional vertebrate phenotyping
Carlos Pardo-Martin,Carlos Pardo-Martin,Amin Allalou,Amin Allalou,Jaime Medina,Peter M. Eimon,Carolina Wählby,Carolina Wählby,Mehmet Fatih Yanik +8 more
TL;DR: High-throughput optical projection tomography with micrometer resolution and hyperdimensional screening of entire vertebrates in tens of seconds using a simple fluidic system are demonstrated.
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.