Model based approach for Detection of Architectural Distortions and Spiculated Masses in Mammograms
Journal Title: International Journal on Computer Science and Engineering - Year 2011, Vol 3, Issue 11
Abstract
This paper investigates detection of Architectural Distortions (AD) and spiculated masses in mammograms based on their physical characteristics. We have followed a model based approach which separates the abnormal patterns of AD and spiculated masses from normal breast tissue. The model parameters are retrieved from Gabor filters which characterize the texture features and synthetic patterns were generated using pplanes to retrieve specific patterns of abnormalities in mammographic images. In addition, eight discriminative features are extracted from region of interest (ROI) which describes the patterns representing AD and spiculated masses. Support vector machine (SVM) and Multi-layer Perceptrons (MLP) classifiers are used to classify the discriminative features of AD and spiculated masses from normal breast tissue. This study concentrates on classifying AD and spiculated masses from the ones which actually are normal breast parenchyma. Our proposal is based on the texture pattern that represents salient features of AD and spiculated mass. Once the descriptive features are extracted SVM and MLP classifiers are used. We have used receiver operating characteristic curve (ROC) to evaluate the performance and we have compared our method with several other existing methods. Our method outperformed other existing methods by achieving 90% of sensitivity, 86% specificity in distinguishing AD from normal breast tissue and 93% sensitivity and 88% specificity in classifying spiculated mass from normal breast parenchyma. In first stage of this study we consider ROI’s that include AD, spiculated masses and normal breast tissue as input. Our method was tested on 190 ROI’s( 19 AD , 19 spiculated mass and 152 normal breast tissue) from Mini-MIAS database and 150 ROI’s( 23 AD , 30 spiculated mass and 97 normal breast tissue ) collected from DDSM database. In the second stage we have applied SVM classification model on whole images and the performance is analyzed by plotting Free Response Operating Characteristic (FROC) curves. SVM classifiers achieved 96% sensitivity with 9.6 false positives per image in detection of spiculated mass and 97% sensitivity with 6.6 false positives per image while detecting AD in digital mammograms.
Authors and Affiliations
Minavathi , Murali. S. , M. S. Dinesh
Keywords
Related Articles
- EP ID EP150470
- DOI -
- Views 123
- Downloads 0
Software Reliability Growth Models for the Safety Critical Software with Imperfect Debugging
In this paper, we will investigate how to perform he log-logistic testing-effort function (TEF) into different software reliability growth models based on non-homogeneous Poisson process (NHPP). The models parameters are...
Walsh Transform over Row Mean and Column Mean using Image Fragmentation and Energy Compaction for Image Retrieval
Always the thrust for better and faster image retrieval techniques has nourished the research in content based image retrieval. The paper presents 32 novel image retrieval techniques using the feature vectors obtained by...
ENERGY CONSERVATION IN CLOUD ENVIRONMENTS USING ALTERNATIVE EMAIL-ID APPROACH
(100%)Cloud computing is a new Model for deliver and accessing the services over the Internet. So cloud provider responsibility to verify the user or client is Authorized or not.For this purpose cloud provider shall prov...
Printed and Handwritten Mixed Kannada Numerals Recognition Using SVM
A mixer of printed and handwritten numerals may appear in a single document such as application forms, postal mail, and official documents. The process of identifying of such mixed numerals and sending it to respective O...
Efficient construction of Optimal Binary Search Trees using Data Preprocessing to improve Quality and Attribute Post computing to save Space and time through modified Dynamic Programming Technique
There are various methods of handling Optimal Binary search trees in order to improve the performance. One of the methods is Dynamic programming which incurs O(n3) time complexity to store involved computations in a tabl...