PRE-PROCESSING OF IMAGES FOR THE DIAGNOSIS OF BREAST CANCER

ANNAVARAPU JAGADISH KUMAR, A V DATTATREYA RAO, K KARTEEKA PAVAN

Abstract


Now a days the diagnosis of breast cancer is done through the analysis of breast images. The primary object of breast imaging is to optimize the early and accurate diagnosis of breast abnormalities based on mammography. Here the term diagnosis refers to classifying a given mammogram into one of the following classes.
1. Calcifications (CALC) 2. Circumscribed (CIRC) 3. Speculated (SPIC) masses 4. Ill-defined (MISC) masses 5. Architectural distortions (ARCH)  6. Asymmetry(s (ASYM) 7. Normal (NORM) masses. The captured image is pre processed for removing digitization noise, suppression of artifacts and separating back-ground and segmenting pectoral muscles in order to find Region of Interest (ROI). Here an attempt is made to present various pre-processing algorithms and to illustrate them by means of a live image.


پاراگلایدر Full Text: PDF

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

ISSN : 2251-1563