Sharif Digital Repository

A hybrid algorithm of a particle swarm optimization and a fuzzy rule-based classification system is proposed in this study to diagnose breast cancer. Two orthogonal and triangular types of fuzzy sets are applied to represent the input variables. In additional, different input membership functions are considered to increase the classification accuracy. The performance of the proposed hybrid algorithm is studied using a classification accuracy measure on the Wisconsin breast cancer dataset. The results of the comparison using different training data sets show the higher performance of the proposed methodology  

in this paper we present an integrated classifier that is used in mammogram MR-image for classification of breast cancers and abnormalities using a Multi-stage classifier, the method developed here first classifies mammograms into normal and abnormal and then for abnormal cases determines that if the case cancer is benign or malignant and also determine the type of breast cancer. In this paper there are two main topics that must be considered. First one is selection of good features and second is designing a good structure for classifier. In this study, the features are a combination of some features that are extracted from Spatial Grey Level Dependency matrix and some statistical descriptor... 

The core-shell nanofibers, produced by the coaxial electrospinning method, are good candidates for delivery of anticancer drugs due to their continuous release without initial burst release. In this work, the N-carboxymethyl chitosan (N-CMCS)-polyvinyl alcohol (PVA)/poly(ε-caprolactone) (PCL) composite and core-shell nanofibers were prepared by two-nozzle and coaxial electrospinning techniques, respectively. Doxorubicin (DOX) as an anticancer drug was loaded into the N-CMCS/PVA/PCL nanofibers fabricated by two-nozzle and coaxial electrospinning. The performance of nanofibers was compared for the adsorption and controlled release of DOX against MCF-7 breast cancer cells death in vitro. The... 

The core-shell nanofibers, produced by the coaxial electrospinning method, are good candidates for delivery of anticancer drugs due to their continuous release without initial burst release. In this work, the N-carboxymethyl chitosan (N-CMCS)-polyvinyl alcohol (PVA)/poly(ε-caprolactone) (PCL) composite and core-shell nanofibers were prepared by two-nozzle and coaxial electrospinning techniques, respectively. Doxorubicin (DOX) as an anticancer drug was loaded into the N-CMCS/PVA/PCL nanofibers fabricated by two-nozzle and coaxial electrospinning. The performance of nanofibers was compared for the adsorption and controlled release of DOX against MCF-7 breast cancer cells death in vitro. The... 

Breast cancer is regarded as one of the most frequent mortality causes among women. As early detection of breast cancer increases the survival chance, creation of a system to diagnose suspicious masses in mammograms is important. In this paper, two automated methods are presented to diagnose mass types of benign and malignant in mammograms. In the first proposed method, segmentation is done using an automated region growing whose threshold is obtained by a trained artificial neural network (ANN). In the second proposed method, segmentation is performed by a cellular neural network (CNN) whose parameters are determined by a genetic algorithm (GA). Intensity, textural, and shape features are... 

Microfluidics based systems could be useful for drug discovery as they allow for miniaturization and could potentially be run as multiple parallel cell based assays. Such miniaturization allows assays at single cell level and reduces the amount of test material needed, which, in the case of natural product extracts, simplifies the preparation. Thyme species extracts have been reported to show some promising anti-cancer effects. In the present work, we used a microfluidics based system to study the effects of Thymus kotschyanusm Boiss plant extract on two human breast cancer cells lines which are MDA-MB-231 and MCF-7. For better understanding a single cancer cell death mechanism and a flow... 

In this study, a folic acid-functionalized niosome was formulated and loaded with letrozole and curcumin as a promising drug carrier system for chemotherapy of the breast cancer cells. The formulation process was optimized by varying the type of Span 80 and total lipid to drug ratio, where Span 80 and lipid to drug molar ratio of 10 resulted in the niosomes with maximum encapsulation of both drugs but minimum size. The developed niosomal formulation showed a great storage stability up to one month with the small changes in drug encapsulation efficiency and size during the storage. In addition, they showed a pH-dependent release behaviour with slow drug release at physiological pH (7.4) while... 

In this paper we will address two major problems in mammogram analysis for breast cancer in MR-images. The first is classification between normal and abnormal cases and then, discrimination between benign and malignant in cancerous cases. Our proposed method extracts textural and statistical descriptive features that are fed to a learning engine based on the use of Support Vector Machine learning framework to categorize them. The obtained results show excellent accuracy in both classification problems, that proves the appropriate combination of our features and selecting powerful classifier i.e. Support Vector Machine leads us to a brilliant outcome