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A novel technique to analyze mammography images for breast cancer treatment

机译:分析乳腺钼靶图像以治疗乳腺癌的新技术

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Cancer is a group of diseases that may start in any body-organ such as breast; it involves abnormal cell growth and spreads to the entire body and the cancer patient may die. Mammography is a familiar method to detect breast cancer of human body. But the disadvantage of a typical mammography technique is of poor contrast; so that, micro calcifications can be overlooked by doctors while using mammograms. In this work, we propose a novel computer-assisted technique to assess mammogram images for breast cancer treatment using some commonly available tools. Our proposed methodology selects suspicious areas on images, hidden attributes are extracted from those selected areas, analyzes the extracted values, and assess the images as benign or malignant based on the extracted values. This work is used by Mammogram images from the Digital Database for Screening Mammogram (DDSM) and Mammographic Image Analysis Society (MIAS). Matrix Laboratory (MATLAB) tool is used to extract the feature values from the images. According to the experimental results, the proposed technique shows potential to accurately analyze the suspicious regions into benign and malignant. We believe that is because the suspicious regions are converted into equivalent numeric values. We plan to extend the proposed image analysis technique to study three-dimensional (3D) medical imaging.
机译:癌症是可能从任何身体器官(如乳房)开始的疾病。它涉及异常的细胞生长并扩散到整个身体,癌症患者可能会死亡。乳房X线照相术是检测人体乳腺癌的一种熟悉的方法。但是,典型的乳腺摄影技术的缺点是对比度差。因此,在使用乳房X光照片时,医生可能会忽略微小的钙化。在这项工作中,我们提出了一种新颖的计算机辅助技术,可以使用一些常用的工具来评估乳房X线照片对乳腺癌的治疗效果。我们提出的方法选择图像上的可疑区域,从这些选定区域中提取隐藏属性,分析提取的值,并根据提取的值将图像评估为良性或恶性。来自数字数据库的乳房X线照片图像用于筛查乳房X线照片(DDSM)和乳房X线照片图像分析协会(MIAS)。矩阵实验室(MATLAB)工具用于从图像中提取特征值。根据实验结果,提出的技术显示了将可疑区域准确分析为良性和恶性的潜力。我们认为这是因为可疑区域被转换为等效的数值。我们计划将提出的图像分析技术扩展到研究三维(3D)医学成像。

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