Breast cancer is the second dangerous carcinoma among aged women in the world. In
order to reduce the breast cancer-related death, an efficient Computer Aided Diagnosis …

This paper presents a comparative study between wavelet and curvelet transform for breast
cancer diagnosis in digital mammogram. Using multiresolution analysis, mammogram …

A new methodology for automatic feature extraction from biomedical images and
subsequent classification is presented. The approach exploits the spatial orientation of high …

The imaging plays a central role in the diagnosis of brain tumors. An efficient algorithm is
proposed in this paper for brain tumor detection based on digital image segmentation. Brain …

Breast microcalcifications are an important primary radiological indicator of breast cancer.
However, microcalcification classification and diagnosis may be still challenging for …

This paper presents an approach for breast cancer diagnosis in digital mammogram using
curvelet transform. The motivation of this approach is the desire of using the advantages of …

A new methodology to automatically extract features from mammograms is presented. The
approach is based on a combination of the discrete wavelet transform and the Gabor filter …

In order to verify tongueprint images, three approaches for texture analyses were considered
and their performances are compared. They are wavelet transform, Gabor filter, and spectral …

Computer Aided Diagnosis (CAD) systems play an important role in early detection of breast
cancer. In this study, we propose a CAD system based on a novel feature set for detection of …

A new methodology to automatically extract features from mammograms for classification is
presented. The approach consists of combining the discrete wavelet transform (DWT) and …