introduction in recent years methods based on radio frequency waves have been used for detecting breast cancer. using theses waves leads to better results in early detection of breast cancer comparing with conventional mammography which has been used during several years. materials and methods in this paper, a new method is introduced for detection of backscattered signals which are received by...

background: transvaginal ultrasound is one of the most common means to examine endometrial cavity lesions although its negative results are more valuable. saline sonohysterography can reduce the number of false negative rates of endometrial lesions diagnoses in tamoxifen consumers. the objective of this study was to determine the diagnostic values of saline infusion sonohysterography (sis) and ...

this paper introduces a novel methodology for the segmentation of brain ms lesions in mri volumes using a new clustering algorithm named scpfcm.  scpfcm uses membership, typicality and spatial information to cluster each voxel. the proposed method relies on an initial segmentation of ms lesions in t1-w and t2-w images by applying scpfcm algorithm, and the t1 image is then used as a mask and is ...

Background: Multiple Sclerosis (MS) is a degenerative disease of central nervous system. MS patients have some dead tissues in their brains called MS lesions. MRI is an imaging technique sensitive to soft tissues such as brain that shows MS lesions as hyper-intense or hypo-intense signals. Since manual segmentation of these lesions is a laborious and time consuming task, automatic segmentation ...

methods in this research, we utilized the chaos theory and fractal analysis in the interpretation of breast tumors on dce-mri. this cross-sectional study was done at pardisnoor imaging center during years 2015 and 2016 in iran. our sample size was 18 mass lesions, which were randomly selected among patients with birad 3 and birad 4 classification by the expert radiologist. the analysis was perf...

Characterization of breast lesions is an essential prerequisite to detect breast cancer in an early stage. Automatic segmentation makes this categorization method robust by freeing it from subjectivity and human error. Both spectral and morphometric features are successfully used for differentiating between benign and malignant breast lesions. In this thesis, we used empirical mode decompositio...

• Accurate diagnosis of high-risk benign breast lesions is crucial since they are associated with an increased risk of invasive breast cancer development. • Since it is not yet possible to identify the occult cancer patients without surgery, this limitation leads to retrospectively unnecessary surgeries. • Here, we present a computational pathology pipeline for histological diagnosis of high-ri...

RATIONALE AND OBJECTIVES The goal of the study is to develop a technique to achieve accurate volumetric breast tissue segmentation using magnetic resonance imaging (MRI) data. This segmentation can be useful to aid in the diagnosis of breast cancers and to assess breast cancer risk based on breast density. Tissue segmentation is also essential for development of acoustic and thermal models used...