Proceedings ArticleDOI
Medical Images Edge Detection Based on Mathematical Morphology
Zhao Yu-qian,Gui Wei-hua,Chen Zhen-cheng,Tang Jing-tian,Li Ling-yun +4 more
- Vol. 2005, pp 6492-6495
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TLDR
A novel mathematical morphological edge detection algorithm is proposed to detect the edge of lungs CT image with salt-and-pepper noise and the experimental results show that the proposed algorithm is more efficient for medical image denoising and edge detection than the usually used template-based edge detection algorithms and general morphologicalEdge detection algorithms.Abstract:
Medical images edge detection is an important work for object recognition of the human organs and it is an important pre-processing step in medical image segmentation and 3D reconstruction. Conventionally, edge is detected according to some early brought forward algorithms such as gradient-based algorithm and template-based algorithm, but they are not so good for noise medical image edge detection. In this paper, basic mathematical morphological theory and operations are introduced at first, and then a novel mathematical morphological edge detection algorithm is proposed to detect the edge of lungs CT image with salt-and-pepper noise. The experimental results show that the proposed algorithm is more efficient for medical image denoising and edge detection than the usually used template-based edge detection algorithms and general morphological edge detection algorithmsread more
Citations
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Morphology filter bank for extracting nodular and linear patterns in medical images.
TL;DR: A morphology filter bank is developed that creates multiresolution representations of an image that produces nodular and linear patterns at each resolution level and can be used to perfectly reconstruct the original image from these decomposed patterns.
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Cystoscopic Image Classification by Unsupervised Feature Learning and Fusion of Classifiers
TL;DR: In this paper, a pre-trained convolutional neural network (CNN) is employed to extract high level semantic features and the number of features is reduced using Principal Component Analysis (PCA) followed by Linear Discriminant Analysis (LDA) to avoid curse of dimensionality issue.
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Hardware Implementation of Bone Fracture Detector Using Fuzzy Method Along with Local Normalization Technique
TL;DR: A new method for bone fracture detection is proposed and its performance is validated through real-time implementation and results show that the proposed method give superior performance than the existing method.
Proceedings ArticleDOI
A Simple Way to Realize the Accurate Detection of Cells' Edge
Jiajia Ma,Xiaona Lv,Shoujuan Yu +2 more
TL;DR: A new mathematical morphological and threshold segmentation edge detection algorithm is proposed to detect the edge of cell image with white noise and results show that the new approach is more effective than traditional methods to reduce the impact of noise on test results.
Journal Article
Segmentation of Brain Tumor in MRI using Multi-structural Element Morphological Edge Detection
M Aysha Bava,Sifna N. Shajahan +1 more
TL;DR: A new method is proposed which segments the brain tumortissues from MR images with noise and Intensity Inhomogeneity artifact, using themulti-structural element morphological algorithm to segment the tumor tissues.
References
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Book
Image Analysis and Mathematical Morphology
TL;DR: This invaluable reference helps readers assess and simplify problems and their essential requirements and complexities, giving them all the necessary data and methodology to master current theoretical developments and applications, as well as create new ones.
Journal ArticleDOI
Detection of Intensity Changes with Subpixel Accuracy Using Laplacian-Gaussian Masks
A. Huertas,Gerard Medioni +1 more
TL;DR: A system that takes a gray level image as input, locates edges with subpixel accuracy, and links them into lines and notes that the zero-crossings obtained from the full resolution image using a space constant ¿ for the Gaussian, are very similar, but the processing times are very different.
Journal ArticleDOI
Morphologic edge detection
TL;DR: The blur-minimum morphologic edge operator is defined, its inherent noise sensitivity is less than the dilation or the erosion residue operators, and it is less computationally complex than the facet edge operator.
Journal ArticleDOI
A new algorithm for image noise reduction using mathematical morphology
TL;DR: The paper describes the MIC algorithm in detail, discusses the effects of parametric variations, presents the results of a noise analysis and shows a number of examples of its use, including the removal of scanner noise.
Journal ArticleDOI
Differential morphology and image processing
TL;DR: The analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms are viewed as a unified area in nonlinear image processing, which is called differential morphology, and its potential applications to image processing and computer vision are discussed.