论文标题
基于图像处理的肝癌检测分析
Analysis of liver cancer detection based on image processing
论文作者
论文摘要
医学成像是检测医学内部并发症的最重要工具。如今,随着图像处理技术的发展以及将照片的大小更改为数字医学成像领域中更高分辨率的图像,有一个有效且准确的系统来分割此信息。出于多种原因,异质性,噪音和对比度的现实世界图像至关重要。医学中的数字图像分割用于诊断和治疗分析,这对医生非常有帮助。在这项研究中,我们旨在更准确地检测肝癌的肝癌照片,因为对肿瘤的准确和及时检测在患者的生存和生命中非常重要。本文的目的是简化与MR图像研究有关的令人讨厌的研究问题。肝脏是转移性疾病最通用的第二个器官,是肝癌是全球死亡的重大原因之一。没有健康的肝脏,一个人将无法生存。这是威胁生命的疾病,对于医学和工程技术人员来说都是非常具有挑战性的。医疗图像处理被用作检测肿瘤的非侵入性方法。具有肝肿瘤生存的机会很大程度上取决于肿瘤的早期检测,然后将其分类为癌和非癌性肿瘤。用于自动检测大脑的图像处理技术包括预处理和增强,图像分割,分类和体积计算,已开发出用于检测肝肿瘤以及用于肿瘤诊断的不同肝脏肿瘤或不同肝脏TOM或检测方法的方法。检测和诊断肝肿瘤的新方法。
Medical imaging is the most important tool for detecting complications in the inner body of medicine. Nowadays, with the development of image processing technology as well as changing the size of photos to higher resolution images in the field of digital medical imaging, there is an efficient and accurate system for segmenting this. Real-world images that for a variety of reasons have poor heterogeneity, noise and contrast are essential. Digital image segmentation in medicine is used for diagnostic and therapeutic analysis, which is very helpful for physicians. In this study, we aim at liver cancer photographs, which aim to more accurately detect the lesion or tumor of the liver because accurate and timely detection of the tumor is very important in the survival and life of the patient.The aim of this paper is to simplify the obnoxious study problems related to the study of MR images. The liver is the second organ most generic involved by metastatic disease being liver cancer one of the prominent causes of death worldwide. Without healthy liver a person cannot survive. It is life threatening disease which is very challenging perceptible for both medical and engineering technologists. Medical image processing is used as a non-invasive method to detect tumours. The chances of survival having liver Tumor highly depends on early detection of Tumor and then classification as cancerous and noncancerous tumours. Image processing techniques for automatic detection of brain are includes pre-processing and enhancement, image segmentation, classification and volume calculation, Poly techniques have been developed for the detection of liver Tumor and different liver toM oR detection algorithms and methodologies utilized for Tumor diagnosis. Novel methodology for the detection and diagnosis of liver Tumor.