Identification of Microcalcifications for Early Signs of Breast Cancer using LabView

Abstract

Breast cancer is the second-most common and leading cause of cancer death among women. It has become a major health issue in the world over the years, and it has increased drastically in recent years. Early recognition is an effective way to diagnose and manage breast cancer. Mammography is an efficient imaging technique for detection and diagnosis of breast pathological disorders at the early stage. The problems in mammography images such as high brightness value, dense tissues, noise and inefficient contrast level make analysis of these images a hard task for physicians for identification of diagnostic signs such as microcalcifications and masses. This paper presents algorithms which are combination of image processing techniques to remove noise and enhancement of mammography images for identification of microcalcifications. Efficient methods such as use of wavelets and adaptive histogram equalization techniques, along with fusion techniques are used for image enhancement to detect microcalcifications. The images for experimentation are taken from MIAS database.

Keywords: LabVIEW, breast cancer, micro calcification, wavelet decomposition

Cite this Article

Meharunnisa SP, Suresh K, Ravishankar M. Identification of Microcalcifications for Early Signs of Breast Cancer using LabView. Journal of Instrumentation Technology & Innovations. 2015; 5(1): 1–5p.