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This paper investigates the use of neural networks to detect and locate early breast cancer using a simple feed-forward back-propagation neural network. In order to test the proposed algorithm, an electromagnetic simulator is used to build a three-dimensional breast model. Spherical tumors of radii 1 mm, 2 mm, 4 mm, and 5 mm are assumed to be at different locations in the breast model. An ultra-wideband...
Ultra-wideband (UWB) microwave imaging is a promising technique for detecting early stage breast cancer, which exploits the significant contrast in dielectric properties between normal and malignant breast tissues. In this paper, we have proposed a new modified compensation method and beamforming technique for microwave imaging. We used a three dimensional (3-D) Finite Integration Technique (FIT)...
A cell culture monitoring platform, called Sensing Cell Culture Flask (SCCF), together with results from measurements in tumor cell cultures is presented. The SCCF can be equipped with oxygen, NO, pH and temperature sensors. In this work measurements from an amperometric oxygen sensor array are shown. Two different cell lines from breast cancer and a brain tumor were tested. Incubation was done under...
In this paper, we designed a Computer-Aided-Diagnosis (CAD) system for lesion detection in breast MR images. The CAD process begins with analysis of MR images to detect the existence of lesion. If lesion exists, it is then coloured based on its type; benign, suspicious or malignant. Our CAD system enables better visualization of the lesions and improves accuracy as well as speed for breast cancer...
Recent studies on the geometry of fractals indicate that tumors with irregular shapes can be utilized for the study of the morphology and diagnosis of cancerous cases. In this paper, we deal with the fractal modeling of the mammographic images and their background morphology. It is shown that the use of fractal modeling as applied to a given image can clearly discern cancerous zones from noncancerous...
Mining techniques are needed to extract important information from huge high dimensional gene expression sets. Targeting unique expression behavior as over/under-expression is specific to gene expression data and is needed to explore another direction in the relation of genes to tumor conditions. This research proposes criteria for filtering over-expression genes, identifying over-expression related...
Different genes have different biological functions, these functions interactions between genes, moreover they play an important role in gene regulatory networks. In the recent cancer research field, a definite conclusion for the regulatory mechanisms of tumor genesis and metastasis has yet been found. Therefore we will apply oncogenes and suppressor genes from ovarian carcinoma micro array data analysis,...
Purpose To investigate the expression of small G protein R-Ras in breast cancer and to explore the significance of R-Ras, expression in the carcinogensis and development of breast carcinoma, and we also analysed the correlation of R-Ras expressions with ER, PR. Methods Real time quantitative reverse transcription polymerase chain reaction (RQ-RT-PCR) technique was applied for detecting R-Ras expression...
The paper presents some recent advances concerning a non-invasive microwave technique which is investigating living structures. A thermogram is plotted, obtained by microwave radiometry. Rigorous scientific studies have shown that the thermo-effect is accompanying growing tumors and atypical developing tissues. Early breast cancer structures are highlighted by this method, two cases being detected:...
Computer aided diagnosis (CAD) paradigms have gained currency for discriminating malignant from benign lesions in ultrasound breast images. But even the most sophisticated investigators often rely on one-dimensional representations of the image in terms of its scanlines. Such vector representations are convenient because of the mathematical tractability of one-dimensional time-series. However, they...
This work aims at selecting useful features in critical angles and distances by Gray Level Co-occurrence Matrix (GLCM). In this project, images were labeled based on physician opinion in two groups (malignant or benign). These labeled images were used in classification analysis. Images were opened and read in Matlab software. The tumors were cropped in rectangular shape manually; then graycomatrix...
The most reliable way to diagnose breast cancer in the current practice of medicine is through pathological examination of a biopsy which has a certain level of subjectivity. To reduce this subjectivity and have a mathematical model for diagnosing breast cancer tissues, a fully automatic method based on microscopic biopsy image is presented. The novel technique is based on a four-step procedure: the...
Ultrasound elastography is a promising technique for the detection of breast cancer. Despite being proven to be a useful method in clinical studies, no studies have looked at directly correlating information in in-vivo ultrasound elastography images with histopathology images (regarded as the gold standard) using image registration. In this paper, expert knowledge from clinicians is utilised as constraints...
Distinguishing cysts from other tumors is a routine clinical practice for diagnosing breast cancer. It has shown that more accurate diagnosis can be achieved by combining elasticity images with traditional B-mode ultrasound images. In this paper, we propose a fully automatic system to detect cysts jointly in both B-mode and elasticity images. It is based on database-guided techniques that learn the...
Mitosis number of tumor cells is an important factor for pathological examinations. Therefore, to get diagnostic information about tumor cells calculating the number of mitosis cells, first of all, it is photographed tumor cells using light microscopy. Number of mitotic cells determined using image processing methods. Aim of the feature extraction for mitosis cell, entropy value, maximum and minimum...
This paper details progress towards a real time palpation simulator. We explore the potential of employing a mass spring system coupled with a haptic interface to realise this. Our motivation lies with enhancing the skills required to detect breast cancer as early as possible. However there are issues in emulating the behaviour of soft tissues using this approach, particularly if the composition of...
We present a study of the spatial variation of nuclear morphology of stromal and cancer-associated fibroblasts in the mouse mammary gland. The work is part of a framework being developed for the analysis of the tumor microenvironment in breast cancer. Recent research has uncovered the role of stromal cells in promoting tumor growth and progression. In specific, studies have indicated that stromal...
Computer-aided prognosis (CAP) is a new and exciting complement to the field of computer-aided diagnosis (CAD) and involves developing computerized image analysis and multi-modal data fusion algorithms for helping physicians predict disease outcome and patient survival. At the Laboratory for Computational Imaging and Bioinformatics (LCIB) at Rutgers University we have been developing computerized...
Vascular endothelial growth factor (VEGF) has been shown to increase the adhesion of human breast cancer cells to human brain endothelium [1]. However, how VEGF accomplishes this is not well understood. We hypothesize that VEGF compromises the integrity of brain microvascular endothelium is one mechanism to increase the tumor cell adhesion. To test our hypothesis, using a Transwell system, we measured...
The initial results for using ultra wideband pulse to achieve strain imaging of breast are presented. In the proposed method, the breast is inserted between two horizontal plates. The upper plate, which includes an array of ultra wideband antennas, is attached to a pressing tool, whereas the lower plate is fixed. Each of the antennas at the top plate is used to send an ultra wideband pulse to penetrate...
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