搜索资源列表
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MICCAI2008脑影像分割文章，包括Interactive Liver Tumor Segmentation using Graph-cut and watershed等-Brain image segmentation MICCAI2008 articles, including the Interactive Liver Tumor Segmentation using Graph-cut and watershed, etc.
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模糊c均值算法，该代码可实现脑肿瘤的分割，效果不错。代码中的GUI直接运行好像有问题，要重新编译。-this code is about FCM.it can carry out the segmentation of brain tumor .the GUI need to compile at the beginning and cannot use it directly
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对MR脑肿瘤图像进行分割,并对分割的结果进行矩描述。方法 在分析当前常用的医学图像分割方法
的基础上,提出一种基于形变模型的医学图像分割方法,并给出了相应的理论算法模型和实现步骤,最后用Visual C ++
6·0编程,并对MR脑肿瘤图像进行分割实验
-MR images of brain tumor segmentation, and segmentation results Moment. Methods used in the analysis of the current
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A Texture based Tumor detection and automatic Segmentation. A thesis written in detecting tumors in x-ray or CT images. Field is into image processing.
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a Method for Applying Morphological Watershed Segmentation on Brain tumor MRI Data-a Method for Applying Morphological Watershed Segmentation on Brain tumor MRI Data...
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用形态学方法和区域增长法进行MRI脑肿瘤图像分割-By morphology and region growing method for MRI brain tumor segmentation
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HMRF MRI brain tumor segmentation
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MRI脑肿瘤分割matlab代码，内面的gui要重新编译才能运行-MRI brain tumor segmentation matlab code, gui inner surface to be recompiled to run
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1、读取显示所给PET图像（SE2\IM210）。
2、学习imhist函数，画出所给PET图像的直方图。
3、根据直方图为该PET图像选择合适的显示窗（imshow参数），使胸
部轮廓等解剖结构可见。
4、根据直方图选择合适阈值，分割肿瘤区域与正常区域，计算肿瘤区
域内图像灰度均值、方差、最大值及最小值。-1 give PET images displayed, read (SE2 \ IM210).
2, learning, imhist function, draw
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基于标准FCM算法的mri脑肿瘤图像分割-MRI brain tumor image segmentation based on standard FCM algorithm
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用于医学图像处理中肺部的分割算法，以分水岭算法为代表的分割方法-Segmentation algorithm for medical image processing in the lungs, as represented in the watershed segmentation algorithm
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基于VS2012平台的肝脏肿瘤分割，使用的是VTK以及itk，主要算法是canny-segmentation of liver with tumor based on itk and vtk by canny
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脑部肿瘤分割编码学习，python编写的程序代码(Brain tumor segmentation coding learning, python programming code)
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在brats 2014数据集上进行脑瘤分割预处理(Brain tumor segmentation pretreatment was performed in the brats 2014 datases)
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用python语言，对脑瘤动态的进行分割，配准等操作(The dynamic segmentation and registration of brain tumor were performed with python)
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在python运行环境下进行脑瘤分割操作的小模型(A small model of brain tumor segmentation under python operating environment)
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对医学图像中的感兴趣区进行标注，比如胸腔肿瘤区域，让不是医学专业的人士也能清楚地看到感兴趣区(Mark a region of interest, such as a thoracic tumor area)
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