Background We compare two methods of breast tissue segmentation: 1) fuzzy c-mean (FCM) clustering [1], an unsupervised learning method that classifies voxels into a specified number of clusters by iteratively minimizing intra-cluster variation, and 2) the support vector machine (SVM) method [2, 3], a supervised learning method that uses training data to construct hyper-planes to minimize the ma...

Microcalcifications can be a very important sign of breast cancer. As their detection is very crucial to further investigation, automatic detection in mammograms can help practitioners to locate missed abnormalities. The aim of this work is to propose a simple method based on fuzzy clustering to efficiently segment microcalcifications. This method which is derived from two existing methods, aut...

Skin cancer has been the most usual and illustrates 50% of all new cancers detected each year. If they detected at an early stage, treatment can become simple and economically. Accurate skin lesion segmentation is important in automated early skin cancer detection and diagnosis systems. The aim of this study is to provide an effective approach to detect the skin lesion border on a purposed imag...

Skin cancer has been the most usual and illustrates 50% of all new cancers detected each year. If they detected at an early stage, treatment can become simple and economically. Accurate skin lesion segmentation is important in automated early skin cancer detection and diagnosis systems. The aim of this study is to provide an effective approach to detect the skin lesion border on a purposed imag...

Introduction Breast cancer is one of the most common types of cancer among women.  Early detection of breast cancer is the key to reducing the associated mortality rate. The presence of microcalcifications clusters (MCCs) is one of the earliest signs of breast cancer. Due to poor imaging contrast of mammograms and noise contamination, radiologists may overlook some diagnostic signs, specially t...

hamartoma of the breast is a rare benign breast lesion which is unfamiliar to most clinicians, although the mammographic features are usually characteristic. hamartomas are composed of ducts, lobules, fat and fibrous tissue. these benign lesions are likely to be increasingly diagnosed because of routine screening and hence clinical awareness is paramount to prevent these lesions from being over...

Segmentation in ultrasound images is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, a segmentation scheme using fuzzy c-means (FCM) clustering incorporating both intensity and texture information of images is proposed to extract breast lesions in ultrasound images. Firstly, the nonlinear structure tensor, which can facilitate to refine the edg...

conclusion our study suggests that breast mri findings of igm have a wide spectrum. rim enhancement patterns are frequently seen on contrast enhanced images, but the imaging findings are nonspecific and cannot be used definitively to distinguish between benign and malignant lesions. patients and methods a retrospective analysis was conducted on 20 patients with igm who had been diagnosed by nee...

introduction breast cancer is one of the most common types of cancer among women.  early detection of breast cancer is the key to reducing the associated mortality rate. the presence of microcalcifications clusters (mccs) is one of the earliest signs of breast cancer. due to poor imaging contrast of mammograms and noise contamination, radiologists may overlook some diagnostic signs, specially t...