The segmentation of medical image applying in medical anatomy plays an important role in diagnosis. So the study of medical image arithmetic is very urgent and necessary.
医学图像分割在医学解剖结构的研究，诊断等起着至关重要的作用，因此对医学图像分割算法的研究非常必要。
Image segmentation is applied in a lot of fields such as computer vision, image coding, pattern recognition, medical image and so on.
图像分割在计算机视觉、图像编码、模式识别、医学图像分析等很多领域有着实际的应用。
Results of experiments show that watershed transformation presents a new method for medical image segmentation.
实验结果表明，流域变换为医学图像提供了一种崭新的分割方法。
Image segmentation is a key basis of many higher level image processing activities such as visualization, compression, and image guided medical diagnoses.
图像分割是很多高级图像处理技术(如可视化、图像压缩、医学图像诊断等)的重要基础工作。
Aiming at the task of the organ modeling, this thesis focuses on the techniques of organ contour-detecting, segmentation and modeling based on medical image.
本文针对人体器官重建这一研究课题，对基于医学影像的器官轮廓检测、分割和模型重建等技术进行了深入的研究。
Ultrasound medical image segmentation is the essential step of ultrasound image processing, and it plays a crucial role in both qualitative and quantitative ultrasound image analyses.
超声医学图像分割是对超声图像进行分析的基本步骤，也是利用超声图像进行定性、定量分析的一个至关重要的环节。
Objective to design an automatic segmentation algorithm of certain anatomy structure, with the rapid increasing of medical image data.
目的随着医学图像数据的急剧增长，建立从医学图像中自动分割特定解剖结构的算法。
For the medical image segmentation, a good accuracy of results is very important and helpful for doctors to diagnose the illness and make the right therapeutic schemes.
对于医学图像而言，其分割结果的准确性对医生诊断病情并做出正确的治疗方案至关重要。
Experiment results of over-segmentation, under-segmentation and incorrect segmentation rates show that DCMIS has better validity and correctness than DENCLUE and FCM for medical image segmentation.
实验结果中的欠分割率、过分割率和错误分割率表明DCMIS比DENCLUE和FCM算法有更好的性能和较好的医学图像分割效能。
Image segmentation is one of the basic technologies in remote sensing and medical image processing but it lacks current algorithm for engineering applications.
图像分割是遥感和医学图像处理的基础技术之一，但是目前缺乏工程化通用算法。
The paper focuses on the research of some key medical image processing technologies in chest X-rays, including chest Radiography images enhancement, segmentation and focus recognition of lung.
本文主要研究了医学X光胸片中的几个关键图像处理技术，主要包括X光胸片图像增强、分割和肺部病灶识别。
In view of the fuzziness of medical image and the requirement in practical application, a watershed segmentation method was proposed based on the dynamic combination rule.
针对医学图像的模糊特点和实际应用的要求，提出了一种基于动态合并准则的分水岭分割方法。
This paper focuses on the image segmentation, which is one of the key problems in medical image processing.
对图像分割进行了研究，这是医学图像处理中的关键问题之一。
Objective To solve one of the most difficult problems in multi dimensional reconstruction of medical ultrasonic images: image segmentation.
目的解决医学图象多维重建中最困难的问题之一：图像分割问题。
The dissertation first introduces the background of medical image segmentation, MRI imaging mechanism, the segmentation target, and the assessment rules for segmentation results.
文章首先介绍了医学图像分割的相关背景、MRI成像机理和分割目标，以及分割结果的评估方法。
Medical image segmentation is a classic problem in image segmentation field, because of the complexity of medical images, so far there is not any all-purpose segmentation method.
医学图像分割是图像分割领域的一个经典问题，由于医学图像的复杂性，到目前为止还不存在一个通用的分割方法。
Image segmentation takes an important place in medical image processing. Different segmentation methods used in medical images cause different effects due to the particularities of medical images.
图像分割在医学图像处理中占有很重要的位置，由于医学图像的一些特殊性，不同的分割方法会产生不同的效果。
Besides, the contrast testing is made separately for the result of improved medical-image segmentation in this thesis.
本文分别对改进的医学影像图像分割结果进行了对比测试。
Objective to improve the automatization and reliability of medical image segmentation.
目的提高图像分割技术的自动化程度和可靠性。
In this paper, the clinical applications of medical image segmentation techniques in vasculature imaging were reviewed.
本文综述图像分割技术在血管图像方面的应用。
Objective evaluation of medical image segmentation algorithms is one of the important steps toward establishing validity and clinical applicability of an algorithm.
对医学图像分割算法的客观评价是推进算法在临床上得到应用的关键。
A clustering segmentation algorithm based on an improved K-means clustering method is used to improve the efficiency and accuracy of 3d medical image segmentation.
为提高三维医学数据场的分割效率和准确率，本文利用特征聚类技术，提出了一种新的基于改进K - means聚类的三维医学数据场的体分割算法。
In recent years medical image segmentation technology is one of the important subjects in medical image processing and analysis research field, and has been a hot issue for researchers.
医学图像分割技术是医学图像处理与分析领域的重要课题之一，也是近年来备受研究人员关注的热点问题。
In recent years medical image segmentation technology is one of the important subjects in medical image processing and analysis research field, and has been a hot issue for researchers.
医学图像分割技术是医学图像处理与分析领域的重要课题之一，也是近年来备受研究人员关注的热点问题。
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