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Due to the high variability in tumor morphology and the low signal-to-noise ratio inherent to mammography, manual classification of mammogram yields a significant number of patients being called back, and subsequent large number of biopsies performed to reduce the risk of missing cancer. The convolutional neural network (CNN) is a popular deep-learning construct used in image classification. This...
In this article, we propose an automatic method for the detection and extraction of the tumor on mammogram images. Most methods of detection of a tumor require the extraction of a large number of texture features from multiple calculations. The study first examines a technique of preprocessing images to obtain the Otsu thresholding method to eliminate items that do not belong in. After performing...
This study proposes a unique approach to classify CerbB2 tumor cell scores in breast cancer based on deep learning models. Another contribution of the study is the creation of a dataset from original breast cancer tissues. On the purpose of training, validating and testing with deep learning models cell fragments were generated from sample tissue images. CerbB2 tumor scores were generated for the...
Breast cancer is invasive cancer among world's women above 35 years of age. The most common symptoms of breast cancer are lumps, change in shape/skin colour and liquid oozing out from nipple. Breast cancer mostly starts from breast tissues that are either in lobules or in milk ducts. Ductal carcinoma is the common type of breast cancer starts from milk ducts and spread across the. Women between the...
In developed countries death of women due to breast cancer has become regular. Data mining techniques are used to provide the analysis for the classification and prediction algorithms. The algorithms used here are Naïve Bayes classification algorithm and Naïve Bayes prediction algorithm. The algorithms are used to classify and predict whether the tumour is either benign or malignant. The data used...
Cancer is a disease characterized by abnormal cell growth in the human body. Cancer is evaluated by histopathological examination, which is important for further treatment planning. The tubule formation, mitotic cell count and nuclear pleomorphism are three parameter used for cancer grading. Mitotic cell (MC) count is one of important factor in cancer diagnosis from histopathological images. MC detection...
In Tunisia, breast cancer is the most common cancer among women; it presents the leading cause of female mortality in the age group 35 to 55 years. This paper uses a neural approach based on Kohonen self-organizing maps to perform a classification of tumors (benign and malignant) using a sample of Tunisian women. Empirical results demonstrate the relevance of the approach and show that neural networks...
An increasing number of studies have profiled gene expressions in tumor specimens using distinct microarray platforms and analysis techniques. One challenging task is to develop robust statistical models in order to integrate multi-platform findings. We compare some methodologies on the field with respect to estrogen receptor (ER) status, and focus on a unified-among-platforms scale implemented by...
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...
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:...
Accurate and less invasive personalized predictive medicine relieves many breast cancer patients from agonizingly complex surgical treatments, their colossal costs and primarily letting the patient to forgo the morbidity of a treatment that proffers no benefit. Cancer prognosis estimates recurrence of disease and predict survival of patient; hence resulting in improved patient management. Support...
With the development of modern science, the goal of medical research is not limit to explore a type of disease but more accurate multi-subtypes of this disease. For example breast cancer can be divided into three different subtypes: BRCA1, BRCA2 and Sporadic. Previous work only focuses on distinguishing several pairs of tumors. However, the simultaneous distinguish across multiple disease types has...
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