Saylee M. Gharge

Learn More
Segmenting a MRI images into homogeneous texture regions representing disparate tissue types is often a useful preprocessing step in the computer-assisted detection of breast cancer. That is why we proposed new algorithm to detect cancer in mammogram breast cancer images. In this paper we proposed segmentation using vector quantization technique. Here we(More)
X-ray mammography is the most common investigation technique used by radiologists in the screening, and diagnosis of breast cancer. The ability to improve diagnostic information from medical images can be enhanced by designing computer processing algorithms that is why we proposed new algorithm to detect cancer in mammogram breast cancer images. In this(More)
— Detection of edges in an image is a very important step towards understanding image features. Since edges often occur at image locations representing object boundaries, edge detection is extensively used in image segmentation when images are divided into areas corresponding to different objects. This can be used specifically for enhancing the tumor area(More)
Edge detector is fundamental issue in image analysis. Due the presence of speckle, which can be modeled as a strong, multiplicative noise, edge detection in synthetic aperture radar (SAR) images is extremely difficult. A common approach is to identify edges as local maxima of the gradient magnitude in the gradient direction. We here proposed a new method as(More)
Segmenting a mammographic images into homogeneous texture regions representing disparate tissue types is often a useful preprocessing step in the computer-assisted detection of breast cancer. That is why we proposed new algorithm to detect cancer in mammogram breast cancer images. In this paper we proposed segmentation using vector quantization technique.(More)
Ultrasound imaging (US) is the most widely used and important imaging modality in medical domain. Due to certain artifact such as speckle, segmentation of US image has not remained a trivial task. Two stages segmentation process has been used in this paper to detect the solid mass (cancer) in breast US image. GLCM based texture feature image generation(More)
Segmentation of medical images is very important nowadays since the images for diagnosis by Radiologist are huge in number. In this paper, texture based segmentation algorithms are considered for comparison. The problem with some of these methods is, they need human interaction for accurate and reliable segmentation. Segmentation based on Gray level(More)
The image segmentation is the basic step in the detection of tumors in various medical images. Specially when used for CAD system. Presence of pectoral muscles gives very false results in the detection process. Removing pectoral muscles is a very important issue in Mammograms. This paper address this issues of Pectorial muscles removal from the mammogram(More)