Multi-resolution analysis using integrated microscopic configuration with local patterns for benign-malignant mass classification-Reference-Cited by-同舟云学术

Multi-resolution analysis using integrated microscopic configuration with local patterns for benign-malignant mass classification

Published:2018-02-27 Issue: Volume: Page:
ISSN:
Container-title:Medical Imaging 2018: Computer-Aided Diagnosis
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Author:

Rabidas Rinku,Midya Abhishek,Chakraborty Jayasree,Sadhu Anup,Arif Wasim

Publisher

SPIE

Reference22 articles.

1. American Cancer Society (ACS), “Global cancer facts and figures,” http://www.cancer.Org/acs/groups/content/@research/documents/document/acspc-044738.pdf (3rd Edition 2012).

2. On Combining Morphological Component Analysis and Concentric Morphology Model for Mammographic Mass Detection

3. Detection of masses in mammograms using region growing controlled by multilevel thresholding;Chakraborty,2012

4. Homer, M. J., [Mammographic Interpretation: A Practical Approach], NY: McGraw-Hill (2nd edition).

5. A benign and malignant mass classification algorithm based on an improved level set segmentation and texture feature analysis;Liu,2010

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4. Multi-Resolution Analysis of Edge-Texture Features for Mammographic Mass Classification;Journal of Circuits, Systems and Computers;2019-12-09

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