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
An Adaptive Mean-Shift Framework for MRI Brain Segmentation
Arnaldo Mayer,Hayit Greenspan +1 more
TL;DR: The proposed adaptive mean-shift methodology is utilized in order to classify brain voxels into one of three main tissue types: gray matter, white matter, and cerebro-spinal fluid and is shown to perform well in comparison to other state-of-the-art methods without the use of a preregistered statistical brain atlas.
Journal ArticleDOI
Challenges and methodologies of fully automatic whole heart segmentation: a review
TL;DR: The existing techniques are reviewed and four key techniques including localization of the whole heart, initialization of substructures, refinement of boundary delineation, and regularization of shapes are discussed.
Journal ArticleDOI
Random forest regression for magnetic resonance image synthesis.
TL;DR: An MRI image synthesis algorithm capable of synthesizing full‐head T2w images and FLAIR images and learns the nonlinear intensity mappings for synthesis using innovative features and a multi‐resolution design is described.
Journal ArticleDOI
3-D Fully Convolutional Networks for Multimodal Isointense Infant Brain Image Segmentation
TL;DR: A novel 3-D multimodal fully convolutional network (FCN) architecture is proposed for segmentation of isointense phase brain MR images and it is demonstrated that carefully integrating coarse and dense feature maps can considerably improve the segmentation performance.
Journal ArticleDOI
Computer-aided kidney segmentation on abdominal CT images
TL;DR: An effective model-based approach for computer-aided kidney segmentation of abdominal CT images with anatomic structure consideration is presented and a visualization tool is implemented that will automatically show the renal contour through the method of second-order neighborhood edge detection.
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.