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Minimum gradient included angle pre-integration illumination method of self-adaptive sampling

An adaptive sampling and pre-integration technology, applied in 3D image processing, image data processing, instruments, etc., can solve the problems of small sampling step size, failure to achieve interactive performance, etc., and achieve the effect of enhancing the lighting effect

Active Publication Date: 2013-09-11
ZHEJIANG UNIV OF TECH
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Problems solved by technology

However, in order to obtain high-quality rendering results, using the pre-integration method still requires a small sampling step size, which cannot achieve good interactive performance

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  • Minimum gradient included angle pre-integration illumination method of self-adaptive sampling
  • Minimum gradient included angle pre-integration illumination method of self-adaptive sampling
  • Minimum gradient included angle pre-integration illumination method of self-adaptive sampling

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Embodiment Construction

[0078] The present invention will be further described below in conjunction with accompanying drawing:

[0079] refer to Figure 1 to Figure 5 , an adaptive sampling minimum gradient angle pre-integration lighting method, the adaptive sampling pre-integration lighting algorithm includes the following steps:

[0080] 1) Import medical body data;

[0081] 2) First, establish multiple pre-integration tables with different step lengths. The number of tables can be determined according to the accuracy requirements of the actual application. During the sampling process, adaptive sampling is performed according to the change trend of the scalar field. When the scalar value changes drastically In the area where extreme values ​​(minimum and maximum values) are encountered, a smaller sampling step can be used; while in areas where the scalar value changes relatively gently, the sampling step can be increased accordingly.

[0082] 3) Reconstruct the gradient in the pre-integration seg...

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Abstract

Discloses is a minimum gradient included angle pre-integration illumination method of self-adaptive sampling. The method includes that 1), medical volume data are imported; 2), multiple pre-integration lists with different step lengths are created, the number of the lists can be determined according to accuracy requirements of actual application, in the process of sampling, self-adaptive sampling is performed according to variation trend of a scalar field, small sampling step lengths can be adopted when extreme values are encountered in areas where scalar values vary dramatically; sampling step lengths can be correspondingly increased in areas where scalar values gently vary relatively; 3), gradients in pre-integration segments are reconstructed by means of interpolation reconstruction, the gradient, having the minimum included angle with the illumination direction, in pre-integration sampling segments is calculated, and the gradient is applied to pre-integration illumination rendering, so that illumination effect of local details is enhanced; 4), corresponding color values and opacity are acquired by searching the pre-integration lists with the different step lengths according to the pre-integration segments acquired by a self-adaptive sampling strategy, and volume rendering integration is performed.

Description

technical field [0001] The invention relates to an adaptive sampling minimum gradient angle pre-integration illumination method Background technique [0002] Medical visualization is one of the most active research fields in scientific visualization. It has important practical value in clinical medicine. It marks the advanced level of a country's medical level and is a manifestation of a country's comprehensive strength. With the rapid development of medical equipment such as magnetic resonance imaging (MRI) and computed tomography (CT), it is possible to obtain a relatively clear two-dimensional digital image sequence of a certain tissue inside the human body through medical imaging equipment. These image sequences include Three-dimensional information of various organs in the human body. However, doctors can only use these two-dimensional sequence images to diagnose the patient's condition based on their own clinical experience, which may lead to deviations in diagnosis a...

Claims

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Application Information

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IPC IPC(8): G06T15/00
Inventor 梁荣华孙文杰徐冰王正州吴福理
Owner ZHEJIANG UNIV OF TECH
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