Detection of Abnormal Masses in Mammogram Images
Journal Title: International Journal of Computer Science and Information Technologies - Year 2010, Vol 1, Issue 5
Abstract
Masses in the breast can be located in digital mammogram images by computationally analysing various feature statistics from the image. Any algorithm used to analyse digital mammogram images can be both time-consuming and errorprone because many areas of these images appear to have features that are mass-like but not masses. Thus false positives are produced which detract from the effectiveness of the algorithm. In this paper an efficient-straightforward algorithm to locate and record suspicious areas in a mammogram image is presented. Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common said abnormalities that may indicate breast cancer are masses and calcifications. The challenge is to early and accurately detect to overcome the development of breast cancer, which affects more and more women throughout the world. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. Digital mammogram is one of the best technologies currently being used for diagnosing breast cancer. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram image. In the paper a method is proposed to make a supporting tool to easy and less time consuming of identification of abnormal masses in digital mammography images. The technique uses a form of template matching at multiple scales to locate pixels in the image, which may be part of a mass. The resulting image is adaptively thresholded to a predetermined level of accuracy and then the remaining pixels are grouped together and extracted. The type of masses, orientation of masses, shape and distribution of masses, size of masses, position of masses, density of masses, and symmetry between two pair are clearly sited after proposed method is executed on raw mammogram for easy and early detection abnormality
Authors and Affiliations
Samir Kumar Bandyopadhyay
Keywords
Related Articles
- EP ID EP85231
- DOI -
- Views 167
- Downloads 0
A Model of MULTI-VERIFIER channel e-mailing system using Steganographic scheme
In this paper, we presented a model of privileged channel e-mailing system for Internet communication. It is the model of a real-life secure mailing system for any organization. In this model a sender can send a secret m...
An Efficient Routing scheme for reliable path establishment among Mobile Devices in Heterogeneous Networks
In heterogeneous networks, devices available with varying connectivity help to provide many new opportunities for efficiently utilizing new resources. In mobile ad hoc networks with varying layered a...
Performance Analysis Of Guaranteed Packet Transfer In Coverage Area And Less Coverage Area For MANET
The main challenge in mobile adhoc network is guaranteed transfer of packet within coverage area and less coverage area. The hierarchical clustering is used to increase coverage area to reduce the packet loss in MANET.Th...
Syntactic Sentence Fusion Techniques for Bengali
The present paper describes various syntactic sentence fusion techniques for Bengali language that belongs to the Indo-Aryan language family. Firstly a clause identification and classification system marks clause boundar...
Performance issues on AODV and AOMDV for MANETS
One of the main challenges of MANET is the design of robust routing algorithms that adapt to the frequent and randomly changing network topology. A variety of routing protocols have been proposed and...