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Automatic segmentation method based on self-adaptive external force level set for magnetic resonance images (MRIs) of soft tissue and realization method thereof

A nuclear magnetic image, automatic segmentation technology, applied in image analysis, image data processing, instruments, etc., can solve problems such as boundary leakage and inability to meet

Inactive Publication Date: 2012-09-19
SANITARY EQUIP INST ACAD OF MILITARY MEDICAL SCI PLA
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Problems solved by technology

However, since this method only uses simple gradient information to control the evolution of the curve, boundary leakage often occurs when segmenting images with blurred or discontinuous edges, and it also cannot meet the requirements of human soft tissue MRI image segmentation.

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  • Automatic segmentation method based on self-adaptive external force level set for magnetic resonance images (MRIs) of soft tissue and realization method thereof
  • Automatic segmentation method based on self-adaptive external force level set for magnetic resonance images (MRIs) of soft tissue and realization method thereof
  • Automatic segmentation method based on self-adaptive external force level set for magnetic resonance images (MRIs) of soft tissue and realization method thereof

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[0054] The automatic segmentation of the adaptive external force level set of the soft tissue nuclear magnetic image and the implementation method of the present invention will be described in detail below in conjunction with the embodiments and the accompanying drawings.

[0055] The method for automatically segmenting the adaptive external force level set of the soft tissue nuclear magnetic image of the present invention is based on the property of the opposite sign of the second-order differential on both sides of the zero-crossing point in the image domain, and uses the sign of the second-order differential value as a guide item to drive the target inside the target. Evolution curves outside or intersecting the target are automatically and accurately approached to the edge of the target. At the same time, the model introduces a new boundary function, which can continuously adjust its parameters according to the characteristics of the image to be segmented, so as to ensure t...

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Abstract

The invention provides an automatic segmentation method based on self-adaptive external force level set for magnetic resonance images (MRIs) of soft tissue and a realization method thereof. The automatic segmentation method comprises the steps that object region tissue satisfying a gray threshold is selected under the circumstance of interactive operation; gradient information of a smoothened image is calculated; a curve evolution guiding function is set; a boundary stopping function is set; and if an evolutional curve exceeds the boundary of an object region, parameters of the boundary stopping function are adjusted, then curve evolution is re-conducted and the iteration is conducted again until the evolutional curve is converged within the boundary of the object region. The automatic segmentation method has the characteristics of high real-time performance, high operation efficiency, capability of segmenting multiple discrete regions at the same time, capability of accurately recognizing fuzzy boundaries of the soft tissue of a human body, high segmentation precision, clear image detail characteristics, high intelligent degree, no need of manual intervention, stable and reliable operation, and the like.

Description

technical field [0001] The invention relates to a medical image segmentation method. In particular, it relates to a soft tissue nuclear magnetic image adaptive external force level set automatic segmentation and its implementation method, which has the characteristics of being able to automatically segment target tissues quickly and accurately without manual intervention. Background technique [0002] Image segmentation is one of the classic research topics in the fields of image processing, image analysis and computer vision, and it is also one of the difficulties. Provide basic support for quantitative and qualitative analysis. Due to the different methods of various images, especially medical images, certain random noise is inevitably introduced in the process, and the shape and intensity of the target of interest in the image are very different, so far there is no general method Segmentation suitable for all images. MRI (Nuclear Magnetic Resonance, Magnetic Resonance ...

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Application Information

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IPC IPC(8): G06T7/00
Inventor 魏高峰田丰孙秋明倪爱娟谢新武秦晓丽
Owner SANITARY EQUIP INST ACAD OF MILITARY MEDICAL SCI PLA
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