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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Comparitive Study of Edge Detection using Multi Structural Elements with different parameters
Harpreet Kaur,Gaurav Mittal +1 more
TL;DR: This paper shows that detection of edges is done using multi structural operations with the help of morphological operations and then analyses the results with thehelp of different parameters to give the better result of edge detection.
Proceedings ArticleDOI
Computer Aided Liver Tumour Detector - CALTD
TL;DR: This research proposes a software solution to illustrate the automated liver segmentation and tumour detection using artificial intelligent techniques and overcomes the challenges in medical image processing.
Journal ArticleDOI
Continuous Image Acquisition and Edge Detection Using Morphological Filters and Classical Edge Detection Algorithms in Labview
TL;DR: This paper has compared the results of First order derivatives of Traditional edge detection methods with morphological edge detection method using LabVIEW to find the discontinuities in surface orientation, changes in material properties and variations in scene illuminations.
Journal ArticleDOI
Edge detection based on morphological amoebas
TL;DR: The amoeba-based edge-detection system performed better than the classic edge detectors, and was evaluated both quantitatively and qualitatively for edge detection of images, and compared to classic morphological methods.
Dissertation
Study and Implementation of Morphology for Speckle Noise Removal and Edge Detection
Arpit Singhal,Malkit Singh +1 more
TL;DR: In this paper, the authors propose a solution to solve the problem of the problem: this paper ] of the "missing link" problem, i.i.p.II.
References
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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.
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Detection of Intensity Changes with Subpixel Accuracy Using Laplacian-Gaussian Masks
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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.