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	<title>Bildsegmentierung Archives &#8212; MATLAB Number ONE</title>
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		<title>Automatic Image Segmentation by Dynamic Region Merging</title>
		<link>https://matlab1.com/shop/matlab-code/automatic-image-segmentation-by-dynamic-region-merging/</link>
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		<pubDate>Tue, 08 May 2018 05:32:39 +0000</pubDate>
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					<description><![CDATA[<p>In this project, we proposed a novel method for segmenting an image into distinct components. The proposed algorithm is implemented in a region merging style. We defined a merging predicate P for the evidence of a merging between two neighboring regions. This predicate was defined by the sequential probability ratio test (SPRT) and the maximum likelihood criterion. [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/automatic-image-segmentation-by-dynamic-region-merging/">Automatic Image Segmentation by Dynamic Region Merging</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>Active contours driven by local image fitting energy</title>
		<link>https://matlab1.com/shop/matlab-code/active-contours-driven-by-local-image-fitting-energy/</link>
					<comments>https://matlab1.com/shop/matlab-code/active-contours-driven-by-local-image-fitting-energy/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Thu, 19 Apr 2018 06:24:50 +0000</pubDate>
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					<description><![CDATA[<p>&#160;</p>
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<p>The post <a href="https://matlab1.com/shop/matlab-code/active-contours-driven-by-local-image-fitting-energy/">Active contours driven by local image fitting energy</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>Active contours with selective local or global segmentation: A new formulation and level set method</title>
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					<comments>https://matlab1.com/shop/matlab-code/active-contours-with-selective-local-or-global-segmentation-a-new-formulation-and-level-set-method/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Thu, 19 Apr 2018 04:41:33 +0000</pubDate>
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					<description><![CDATA[<p>In this paper, we proposed a novel region-based ACM for image segmentation which is implemented with a new level set method named SBGFRLS method. The SBGFRLS method reduces the expensive re-initialization of the traditional level set method to make it more efficient. The proposed model implementing with the SBGFRLS method combines the merits of the traditional GAC and C–V models, which [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/active-contours-with-selective-local-or-global-segmentation-a-new-formulation-and-level-set-method/">Active contours with selective local or global segmentation: A new formulation and level set method</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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		<title>Brain MRI Segmentation via Region Based Active Contour Segmentation</title>
		<link>https://matlab1.com/shop/matlab-code/brain-mri-segmentation-via-region-based-active-contour-segmentation/</link>
					<comments>https://matlab1.com/shop/matlab-code/brain-mri-segmentation-via-region-based-active-contour-segmentation/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Tue, 10 Apr 2018 17:49:47 +0000</pubDate>
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					<description><![CDATA[<p>This project developed an algorithm that combined nonlinear filtering, active contour modeling, statistical thresholding, and morphological post-processing into a novel algorithm that can robustly segment brain MRI images. The runtime of the presented algorithm is significantly faster than manual segmentation and other existing semi-automated segmentation workflows, and the algorithm was still very effective at extracting the relevant brain tissue from the MRI [&#8230;]</p>
<p>The post <a href="https://matlab1.com/shop/matlab-code/brain-mri-segmentation-via-region-based-active-contour-segmentation/">Brain MRI Segmentation via Region Based Active Contour Segmentation</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
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