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
Principles and applications of computer graphics in medicine
Franck Vidal,Fernando Bello,Ken Brodlie,Nigel W. John,Derek A. Gould,Roger W. Phillips,Nicholas John Avis +6 more
TL;DR: A comprehensive overview of the state‐of‐the‐art in this exciting field of computer graphics, visualization and virtual environments from the perspective of both computer scientists and practising clinicians is provided.
Journal ArticleDOI
Bone segmentation on whole-body CT using convolutional neural network with novel data augmentation techniques
TL;DR: The CNN-based model achieved accurate bone segmentation on whole-body CT, with generalizability to various scan conditions, and data augmentation techniques enabled construction of an accurate and robust model even with a small dataset.
Journal ArticleDOI
Active Mask Segmentation of Fluorescence Microscope Images
TL;DR: A new active mask algorithm for the segmentation of fluorescence microscope images of punctate patterns that combines the flexibility offered by active-contour methods, speed offered by multiresolution methods, and statistical modeling offered by region-growing methods into a fast and accurate segmentation tool.
Journal ArticleDOI
Quantifying the uncertainty in a hyperelastic soft tissue model with stochastic parameters
TL;DR: In this paper, a simple open-source semi-intrusive computational method to propagate uncertainties through hyperelastic models of soft tissues is presented, which is up to two orders of magnitude faster than the standard Monte Carlo method.
Journal ArticleDOI
Automatic Segmentation of the Prostate on CT Images Using Deep Neural Networks (DNN).
Chang Liu,Stephen J Gardner,Ning Wen,Mohamed A. Elshaikh,Farzan Siddiqui,Benjamin Movsas,Indrin J. Chetty +6 more
TL;DR: A DNN-based algorithm was used to automatically segment the prostate for a large cohort of patients with prostate cancer and the agreement between DNN segmentations and consensus contour was similar to the agreement reported in a previous study.
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.