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Description: Atrous and Multiscale edge detection with Matlab GUI
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Size: 1410048 |
Author: TRUONG SON |
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Description: Prewitt edge detection for mammogram using matlab
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Size: 43008 |
Author: surendiran |
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Description: A Soft-Decision Approach for Microcalcification Mass Identification from Digital Mammogram
By Surendiran.B, Dr.A.Vadivel, Henry Selvaraj
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Size: 164864 |
Author: surendiran |
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Description: Digital Mammogram - Database - websites-Digital Mammogram- Database- websites
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Size: 6144 |
Author: surendiran |
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Description: 该程序用实现寻找钼靶图像中乳腺轮廓。在医学图像处理当中，找到乳腺轮廓有助于简化后绪处理。-This code is used for finding the boudary of the breast in a mammogram.
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Size: 3072 |
Author: yuting |
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Description: ADA and NN based Mammogram Mass Classification using various geometric shape features
Surendiran.B, A.Vadivel
National Conference on Advanced Pattern Mining and Multimedia Computing, APMMC10, Department of Computer Applications, National Institute of Technology, Trichy
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Size: 419840 |
Author: surendiran |
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Description: Mammogram classification
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Size: 268288 |
Author: Mohamed |
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Description: 一种基于地形信息的钼钯图像中肿瘤分割方法,很新的文章，借鉴一下很好-very good
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Size: 1908736 |
Author: 董巍 |
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Description: Mammogram Enhancement
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Size: 98304 |
Author: Ramkumar |
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Description: glcm feature extraction for mammogram images
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Size: 1024 |
Author: nur sener |
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Description: Image Enhancement technique for mammogram images
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Size: 135168 |
Author: mohan |
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Description: segmentation of mammogram images
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Size: 492544 |
Author: yaser ali reyad |
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Description: mixing the phase and amplitude of different images
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Size: 2048 |
Author: dhivya |
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Description: Mammography is one of the available techniques for the early detection of masses or abnormalities which
is related to breast cancer. Breast Cancer is the uncontrolled of cells in the breast region, which may affect
the other parts of the body. The most common abnormalities that might indicate breast cancer are masses
and calcifications. Masses appear in a mammogram as fine, granular clusters and also masses will not have
sharp boundaries, so often difficult to identify in a raw mammogram. Digital Mammography is one of the
best available technologies currently being used for the early detection of breast cancer. Computer Aided
Detection System has to be developed for the detection of masses and calcifications in Digital
Mammogram, which acts as a secondary tool for the radiologists for diagnosing the breast cancer. In this
paper, we have proposed a secondary tool for the radiologists that help them in the segmentation and
feature extraction process.
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Size: 408576 |
Author: yokool |
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Description: In most of the approaches of computer-aided detection of breast cancer, one of the preprocessing steps applied to the mammogram is the removal/suppression of pectoral muscle, as its presence within the mammogram may adversely affect the outcome of cancer detection processes. Through this study, we propose an efficient automatic method using the watershed transformation for identifying the pectoral muscle in mediolateral oblique view mammograms. The watershed transformation of the mammogram shows interesting properties that include the appearance of a unique watershed line corresponding to the pectoral muscle edge. In addition to this, it is observed that the pectoral muscle region is oversegmented due to the existence of several catchment basins within the pectoral muscle
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Size: 1179648 |
Author: yokool |
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Description: A Gabor-filtering method for describing textural features
is proposed, which applies the physical properties of a probability
wave to probability transformation, and computes
textural features
2) An adaptive strategy for feature and filter selection, and
feature weighting, is proposed, which utilizes a user’s relevance
feedback to reduce the redundancy in the representation
and incorporate the user’s information needs in image
retri
3) Integrating both schemes (the Gabor-filtering method and
the adaptive strategy) for content-based mammogram retri
is suggested-A Gabor-filtering method for describing textural features
is proposed, which applies the physical properties of a probability
wave to probability transformation, and computes
textural features
2) An adaptive strategy for feature and filter selection, and
feature weighting, is proposed, which utilizes a user’s relevance
feedback to reduce the redundancy in the representation
and incorporate the user’s information needs in image
retri
3) Integrating both schemes (the Gabor-filtering method and
the adaptive strategy) for content-based mammogram retri
is suggested
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Size: 3072 |
Author: Vishal |
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Description: Mammogram breast cancer image detection MATLAB File
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Size: 24576 |
Author: haniyeh |
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Description: 基于NSCT增强图像细节。使用时要和NSCT放在同一目录下。-Mammogram microcalcification Enhancement using NSCT
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Size: 134144 |
Author: 曾义和 |
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Description: how to mammogram image is enhanced with the help of median filter and adaptive histogram equalization and feature extraction using GLCM in matlab.
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Size: 11367424 |
Author: bul |
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Description: tHIS FILE DESCRIBES THE FEATURE SELECTION TECHNIQUE FOR MAMMOGRAM FEATURES
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Size: 1147904 |
Author: karthikeyan |
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