Diagnosis of cardiovascular disorder by CT images using Machine learning technique

K. Nithyakalyani, S. Ramkumar, S. Rajalakshmi, K. Saravanan
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引用次数: 1

Abstract

Cardiac imaging plays a predominant role in the diagnosis of cardio vascular disorders. The main aim of this project is to diagnosis the cardiac disorders using CT imaging along with a machine learning technique (Artificial neural network). Image processing techniques such as pre-processing, segmentation and classification are using for processing the image. Here segmentation and classification of the CT image plays an important role to diagnose the disorder, for segmentation ANN is being used and for classification SVM is employed both comes under the machine learning techniques. The implementation of machine learning techniques emerges as the artificial intelligence tool that will be of service to diagnosis of cardiovascular diseases. By constructing different algorithms for each process we can obtain précised and automated output. So that, the output of the experiment helps the clinician to diagnose the cardiac disorders more clearly and can be moved to further treatment
基于机器学习技术的CT图像诊断心血管疾病
心脏影像学在心血管疾病的诊断中起着重要作用。本项目的主要目的是利用CT成像和机器学习技术(人工神经网络)来诊断心脏疾病。图像处理技术包括预处理、分割和分类等。这里对CT图像的分割和分类对于诊断疾病起着重要的作用,对于分割使用的是人工神经网络,对于分类使用的是支持向量机,两者都属于机器学习技术。机器学习技术的实现将成为心血管疾病诊断服务的人工智能工具。通过为每个过程构建不同的算法,我们可以获得程序化和自动化的输出。这样,实验的输出可以帮助临床医生更清楚地诊断心脏疾病,并可以进行进一步的治疗
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