NDLI: Analysis of 2D singularities for mammographic mass classification

Content Provider	IET Digital Library
Author	Rabidas, Rinku Chakraborty, Jayasree Midya, Abhishek
Abstract	Masses are one of the prevalent early signs of breast cancer, visible in mammogram. However, its variation in shape, size, and appearance often creates hazards in proper diagnosis of mammographic masses. This study analyses the 2D singularities of masses and their surrounding regions with Ripplet-II transform to classify them as benign and malignant. Since benign and malignant masses may change the orientation patterns of normal breast tissues differently, several textural features including Ripplet-II coefficients and statistical co-variates, derived from the Ripplet-II transformed images, are extracted to quantify the texture information of mammographic regions. The important features are then selected using stepwise logistic regression technique and evaluated using linear discriminant analysis and support vector machine with a ten-fold cross-validation. The best performance in terms of the area under the receiver operating characteristic curve of 0.91 ± 0.01 and 0.83 ± 0.01 and accuracy of 87.28 ± 0.02 and 75.60 ± 0.01 are obtained with the proposed method while experimenting with 58 images from the mini-MIAS and 200 images from the Digital Database for Screening Mammography database, respectively.
Starting Page	22
Ending Page	32
Page Count	11
ISSN	17519632
Volume Number	11
e-ISSN	17519640
Issue Number	Issue 1, Feb (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/11/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2016.0163
Journal	IET Computer Vision
Publisher Date	2016-07-27
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	2D Singularity Analysis Benign Masses Biological Organs Biological Tissues Biology And Medical Computing Biomedical Imaging/measurement Breast Cancer Breast Tissues Cancer Computer Vision And Image Processing Technique Digital Database Image Classification Image Recognition Image Texture Knowledge Engineering Technique Linear Discriminant Analysis Logistic Regression Technique Malignant Masses Mammographic Mass Classification Mammographic Region Mammography Medical Image Processing Patient Diagnostic Method And Instrumentation Probability Theory Radiography And Computed Tomography Receiver Operating Characteristic Curve Regression Analysis Ripplet-II Coefficient Ripplet-II Transform Ripplet-II Transformed Imaging Screening Mammography Database Sensitivity Analysis Statistical Covariates Statistics Stochastic Linearised SCUC Support Vector Machine Ten-fold Cross-validation Textural Feature Texture Information X-Ray Technique X-Rays And Particle Beam
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Mammographic mass classification using filter response patches

Superpixel texture analysis for classification of breast masses in dense background

Development of an intelligent CAD system for mass detection in mammographic images

Curvelet analysis of breast masses on dynamic magnetic resonance mammography

Classification of mammogram using two-dimensional discrete orthonormal S-transform for breast cancer detection

Mammographic mass classification according to Bi-RADS lexicon

Anomaly classification in digital mammography based on multiple-instance learning

Some variants of spiral LBP in texture recognition

Breast mass classification method based on convolutional neural networks

Analysis of 2D singularities for mammographic mass classification

Similar Documents

Mammographic mass classification using filter response patches

Superpixel texture analysis for classification of breast masses in dense background

Development of an intelligent CAD system for mass detection in mammographic images

Curvelet analysis of breast masses on dynamic magnetic resonance mammography

Classification of mammogram using two-dimensional discrete orthonormal S-transform for breast cancer detection

Mammographic mass classification according to Bi-RADS lexicon

Anomaly classification in digital mammography based on multiple-instance learning

Some variants of spiral LBP in texture recognition

Breast mass classification method based on convolutional neural networks

Analysis of 2D singularities for mammographic mass classification