This paper aims at pilot study on multimodality medical image fusion.
本文主要内容是关于多模态医学图像融合的研究和实现。
Multi-modality medical image fusion plays an important role in medical analysis and diagnosis.
多模态医学图像融合在医学图像的分析和诊断上具有极为重要的应用价值。
The new image which is integrated from different modes images called the medical image fusion and the first step of fusion is image registration.
这种将不同模式的图像信息整合成一种新模式的图像称为医学图像的融合，而融合的第一步先要配准。
Medical image registration, as the prerequisite for medical image fusion, is a hot field in the medical image processing and commonly used for clinical diagnosis and treatment.
医学图像配准是医学图像融合的前提，是目前医学图像处理中的热点，具有重要的临床诊断和治疗价值。
The re- search proves that the fusion result of the method is more exact and more suitable to arbitrary medical image fusion with different equipment because of no registration.
研究证明，使用该方法不仅融合的结果更加准确有效，而且无需配准，适用于任意的医学成像设备的影像融合。
Image fusion is fundamental problem in image analysis and processing, and is used widely in medical imaging.
图像融合是图像分析和处理的基本问题，在医学影像领域有着广泛的应用。
As a very important field of information fusion, image fusion has been extensively applied in remote sensing, medical science, computer vision, detecting and identification of military target etc.
图像融合作为信息融合的一个重要领域已广泛应用于遥感、医学、计算机视觉、军事目标探测和识别等多方面。
Image fusion is a key technology on medical images progressing.
图像融合是医学图像处理中的关键技术。
Image fusion plays an even most significant role in the field of modern medical now, and it is the core of research of image technology.
图像融合技术在现代医学中扮演着极其重要的角色，是现代医学图像技术研究的重点。
Image fusion is a research focus of medical image processing. Proper registrations were desired in clinical diagnoses and therapy to obtain complementary information from multi modality images.
医学图像融合是医学图像后处理的研究热点，它充分利用多模式图像，获得互补信息，使临床的诊断和治疗更加准确完善。
Multi-Modality fusion is one of the hottest discussed issues in the current research of medical image processing and it has a deep impact on the cognitive science and clinical treatment.
作为当今医学影像技术研究中的热点问题之一，多模态医学影像融合技术的研究及其研究成果，对认知科学的研究和临床治疗有着重要的意义。
Using the technologies of image fusion, we can combine the multimodality medical image information efficiently which is very helpful for clinical diagnoses and treatment.
利用图像融合技术，将不同模态的医学图像有机地结合在一起，可以充分利用各种医学图像的优点，为临床诊断和治疗提供帮助。
Medical image registration and fusion is an indispensable part of modern medical treatment.
医学图像的配准与熔合是现代医疗中不可或缺的一部分。
Medical image registration and fusion is a crossing research topic of information science, computer image technology and modern medicine.
医学图像配准与信息融合是当代信息科学、计算机图像技术与当代医学等多学科交叉的一个研究领域。
Image fusion is a key technology in medical images progressing.
图像融合是医学图像处理中的关键技术。
Medical image registration as a prerequisite for image fusion, its research is a hot in the area of medical image processing.
医学图像配准作为图像融合的先决条件，它的研究是医学图像处理领域的热点。
To acquire better medical ultrasonic image of diagnosis, image fusion is introduced in ultrasonic imaging.
将它引入医学超声影像中，以期获得更清晰的利于诊断的医学超声图像。
Being an efficient method of information fusion, image fusion has been used in many fields such as machine vision, medical diagnosis, military applications and remote sensing.
图像融合作为一种有效的信息融合技术，已经广泛用于军事、遥感、机器视觉和医疗诊断等领域。
Image fusion technology has been widely used in remote sensing image analysis, machine vision, medical diagnostics, target identification and other fields.
图像融合技术已广泛应用于遥感影像分析、机器视觉、医疗诊断、目标识别等领域。
Image registration is an important subject in medical image processing. It is fundamental for image matching with atlas, image fusion and micrograph reconstruction.
医学图像配准是医学图像处理中的一个重要研究课题，它是图像融合、图像与标准图谱的匹配、显微图像的重建等研究的基础。
This paper presents two feature fusion algorithms of medical image retrieval about endoscopic image based on FCM as follow:first, using color correlogram combining with color texture;
针对医学内窥镜图像，提出两种基于模糊C-均值聚类（FCM）的特征融合算法：融合颜色相关图和图像纹理特征算法以及融合颜色直方图和颜色相关图算法。
A medical image 3-d fusion method is discussed.
本文讨论了医学图象立体融合的实现方法。
The feature fusion of image has more and more important applications, such as in target recognition, medical treatment and biology feature recognition.
而图像融合中的特征级融合在目标识别、医疗诊断以及生物特征识别等领域有着越来越重要的作用。
The feature fusion of image has more and more important applications, such as in target recognition, medical treatment and biology feature recognition.
而图像融合中的特征级融合在目标识别、医疗诊断以及生物特征识别等领域有着越来越重要的作用。
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