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| 基于核磁共振成像的农产品几何模型重构 | |
| 引用本文： | 张建锋,何 勇,王南飞,吴 迪,龚向阳.基于核磁共振成像的农产品几何模型重构[J].农业工程学报,2012,28(21):215-220. |
| 作者姓名： | 张建锋 何 勇 王南飞 吴 迪 龚向阳 |
| 作者单位： | 1. 浙江大学生物系统工程与食品科学学院,杭州 310058 2. 浙江大学唐仲英传感材料及应用研究中心,杭州 310058 3. 爱尔兰国立都柏林大学生物系统工程系,都柏林 Dublin 4 4. 浙江大学医学院附属邵逸夫医院放射科,杭州 310016 |
| 基金项目： | 国家"863"计划项目（2011AA100705）;农业部公益性行业专项（200903044）;浙江省自然科学基金重点项目（Z3090295）;中央高校基本科研业务费专项资金资助 |
| 摘 要： | 为了提高农产品数值模拟的精度,需要为其提供精确的农产品几何模型。该研究以具有不规则几何特征的农产品芒果、香蕉和苹果为试验对象,利用核磁共振成像仪获取的断层切片图像,借助于计算机图形学技术和视觉化工具函数库Visualization Toolkit5.4(VTK),实现了其几何模型的重构。结果表明,3种农产品几何模型的体积值与其真实值之间的误差均小于3%,与标准方法测得结果具有很好的一致性。该研究为农产品几何模型获取提供了一种新的方法,能为农产品数值模拟、有限元分析以及品质检测等提供直接的几何模型支持。 |
| 关 键 词： | 农产品 无损检测 核磁共振成像 不规则形状 几何模型 |
| 收稿时间： | 5/7/2012 12:00:00 AM |
| 修稿时间： | 2012/10/19 0:00:00 |
Geometry modeling reconstruction of agricultural products by magnetic resonance imaging |
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| Zhang Jianfeng,He Yong,Wang Nanfei,Wu Di and Gong Xiangyang.Geometry modeling reconstruction of agricultural products by magnetic resonance imaging[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(21):215-220. | |
| Authors: | Zhang Jianfeng He Yong Wang Nanfei Wu Di and Gong Xiangyang |
| Institution: | 1. College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China; 2. Cyrus Tang Center for Sensor Materials and Applications, Zhejiang University, Hangzhou 310058, China; 3. Biosystems Engineering, University College Dublin, National University of Ireland, Belfield, Dublin 4, Ireland; 4. Department of Radiology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou 310016, China) |
| Abstract: | Modeling and simulation of agricultural products during harvesting, storage, and transportation process are very important issues in agricultural postharvest engineering field. Considering transport phenomena principles involved in the model formulation, a geometry representing the real object is needed to be defined. However, since agricultural products are usually naturally irregular in shape, accurate acquisition of their geometric model becomes essential. In this research, the model reconstruction process which consists of magnetic resonance imaging, image processing and reconstruction method allows obtaining accurate geometric models even for agricultural products with very irregular shapes. Some typical agricultural products with irregular shapes, such as mango, banana and apple, were selected as the experimental samples to reconstruct their geometry models from magnetic resonance imaging data. All NMR data were acquired from a GE whole-body magnetic resonance imaging system with a static magnetic field of 3.0 Tesla. Samples were fixed on a plastic holder and then manually focused to obtain the images. MR images were generated using a fast spin echo sequence with effective echo time of 65 ms, repetition time of 1800 ms, slice thickness of 2 mm, and field of view of 512512 pixels. In order to better acquire the irregular contour curves of each MR image, several image preprocessing steps implemented in MATLAB were applied to all original the MR images, the steps are as follows: (1) gray level transformation of the original gray level images; (2) median filtering for noise reduction and image quality enhancement; (3) segmentation through an adaptive threshold segmentation algorithm; (4) image filling and ensure each image only has a single contour curve. A procedure to obtain geometric models of irregular agricultural products was developed by the computer image graphics technology. The whole model reconstruction process was implemented in Visualization Toolkit 5.4. The contour curves approximating the real boundaries of cross section were correctly assembled by means of a reconstruction technique Marching Cubes algorithm. And then Laplacian mesh smoothing and Quadric Error Metric (QEM) edge folding simplified algorithm were used to enhance the practicality of the reconstruction model. In order to verify the reliability of the reconstructed methods, the obtained geometric models were converted to STL format, and then transformed to a 3D solid object. Then we imported them into a computer aided design software Pro/E to calculate their geometric parameters. Similarly, actual geometric parameters of the samples were measured by a vernier caliper and the water displacement method. Comparing the geometric model of agricultural products with the physical object, it was found that the obtained geometric models were well consistent with real samples, they showed very good agreement in shape, volume and other morphological parameters, and the errors between them were less than 3%. The presented methodology can avoid making great efforts in experimental measurements and consequently development of the geometric models, decreasing error generated from manual data extraction. The method has the significant advantages of producing geometric models of agricultural products that are easy to use in computer aided design software for numerical simulation, finite element analysis and quality detection, etc. This work is expected to be a useful contribution for modeling and simulation of agricultural products in postharvest engineering processes. |
| Keywords: | agricultural products nondestructive examination magnetic resonance imaging irregular shape geometric modeling |
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