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Cancerous masses detection in dense background is a particularly challenging task for even experienced radiologists due to their similarity of intensity with the overlapped normal dense tissues, obscured boundaries and low contrast between mass and surrounding regions. This paper proposes a novel approach for the identification of cancerous regions located in a dense part of a breast. Careful analysis...
In this paper, the computational modeling of the 2D human breast in hyperthermia treatment at 2.45 GHz is studied. The mathematical tool used in this study for investigating the distribution of generated heat is the COMSOL software where the breast is modeled by Pennes' bioheat equation. The model simulation is conducted to investigate the effects of exposure time and power inputs on the cancerous...
This paper presents a study of the impact of image preprocessing techniques on the segmentation and classification of breast lesions on ultrasound. Commonly, image preprocessing performs contrast enhancement and speckle reduction. In this sense, five contrast enhancement techniques and four despeckling methods were combined to generate 20 different image preprocessing schemes. The experiments considered...
Breast cancer is the second most common cancer in the world and the most frequent type of cancer among women (25 % of all cancers). This study used contrast-enhanced 3D subharmonic imaging (SHI) to produce quantitative parametric maps for characterization of breast lesions.
Irregular patterns of micro calcifications in the breast may indicate a malignant cancer tumor. Today early detection is done with x-ray mammography. However, in some women the high density of connective tissue of the breast can limit detection using X-ray imaging. With ultrasound, improved suppression of the connective tissue can be achieved. During breast tissue biopsy ultrasound can also provide...
The ability to visualize breast lesion vascularity and quantify the vascular heterogeneity using contrast-enhanced 3-D nonlinear ultrasound imaging was investigated in a clinical population. Patients (n = 236) identified with breast lesions on mammography were scanned using power Doppler imaging, contrast-enhanced 3D HI, and 3D SHI on a modified Logiq 9 scanner (GE Healthcare). Time-intensity curve...
The search for new potent anticancer drugs that can only target cancer cells, rather than affecting normal tissues is very much commendable. Supramolecular Calixarene (p-tert-butylcalix[4]arene) is a highly promising candidate in this regard and could be modified to enhance preferential cytotoxicity for targeted therapy. Calixarenes are a family of bowl or cone shaped synthetic supramolecular macrocycles,...
Cancer is one of the most prevalent diseases in Europe and the world. Significant correlations between dietary habits and cancer incidence and mortality have been confirmed by the literature. Physical activity habits are also directly implicated in the incidence of cancer. Lifestyle behaviour change may be benefited by using mobile technology to deliver health behaviour interventions. M-Health offers...
The paper presents a mathematical model of prognostic factors in breast cancer, accomplished for a determined period of 60 months. The study was conducted on a group of patients selected from all of the patients with breast cancer treated in the Clinic of Oncology-Radiation of Emergency Hospital “St. Spiridon” Iasi in a period of 3 years. Survival data specific for each prognostic factor was processed,...
Three-dimensional imaging based on radio frequency that exploits the contrast in dielectric properties of tissues may be used as a low-cost, non-invasive and non-ionizing methodology for breast cancer detection. This paper demonstrates the use of various supervised machine learning algorithms in classification of breast tissues into less-dense fatty and dense fibroglandular or malignant classes from...
Determination of disease related biological processes and the estimation of molecular interactions related to these processes are important to understand the underlying mechanism of diseases. In our study we infer gene co-expression networks of breast and colon cancer using miRNA-target gene interactions. Popular information theory based gene network inference algorithms are utilized to infer gene...
In this paper an image reconstruction system and an algorithm for image reconstruction is developed and studied. The purpose is to determine and optimize a reconstruction scheme that is suitable for microwave imaging of breasts, with the purpose to diagnose breast cancer tumors. The present study is based on data generated from realistic breast models and in particular the use of different matching...
Histopathology forms the gold standard for confirmed diagnosis of a suspicious hyperplasia being benign or malignant and for its sub-typing. While techniques like whole-slide imaging have enabled computer assisted analysis for exhaustive reporting of the tissue section, it has also given rise to the big-data deluge and the time complexity associated with processing GBs of image data acquired over...
In this paper, we propose a multi-view deep residual neural network (mResNet) for the fully automated classification of mammograms as either malignant or normal/benign. Specifically, our mResNet approach consists of an ensemble of deep residual networks (ResNet), which have six input images, including the unregistered craniocaudal (CC) and mediolateral oblique (MLO) mammogram views as well as the...
Breast ultrasound is an important complement to mammography that allows differentiating between benign and malignant lesions. The early diagnosis and specialized care for women with breast cancer are indispensable for a better therapeutic result and prognosis of cases. Thereby, it is necessary training professionals to emit trustworthy diagnoses. Here, we set up lesions-like structures in a plasticized...
Cervical cancer is a disease that affects 266,000 deaths worldwide and is the fourth highest incidence of cancer in women. This cancer can be diagnosed through a Pap smear, where a cytopathologist observes a microscopic image of the cervix cells to determine whether the patient is normal or abnormal. The sensitivity and specificity of the Pap smear is known to be respectively 53.4% and 69.2%. Since...
Traditional n-gram feature representation of freetext documents often fails to capture word ordering and semantics, thus compromising text comprehension. Graph-of-words, a new text representation approach based on graph analytics, is a superior method overcoming the limitations by modeling word co-occurrence. In this study, we present a novel application of graph-of-words text description for automated...
Based on various genomic information of chimeric transcript, recent studies used machine-learning methods to predict the oncogenic potentials for chimeric transcripts, however these works ignored transcriptional signature of those chimeric transcripts. Based on clonal evolution theory, we hypothesized that a chimeric transcript is more likely to be an oncogenic ‘driver’ mutation, if the neoplastic...
Computer Aided Diagnosis (CAD) is usually used to assist radiologists while interpreting mammograms and help them improving breast cancer diagnosis accuracy at earlier stages. One of the main breast cancer early indicators is the presence of masses. CAD systems main target is to detect eventual masses from digital mammograms characterize them and evaluate their malignancy. In this paper, we introduce...
Computer Aided Detection (CAD) increases the early detection of breast abnormalities in digital mammogram. Digital mammogram is the low energy and efficient screening tool to detect the breast abnormalities detective of breast abnormalities is carried out by using digital mammogram. The micro calcification and masses are the important sign to detect the breast abnormalities due to low contrast nature...
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