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1. 发明申请

US20130333237A1 CONTINUOUS MICROWAVE FREEZE-DRYING DEVICE 有权
标题翻译：连续微波冷冻干燥装置
公开(公告)号：US20130333237A1
公开(公告)日：2013-12-19
申请号：US13990767
申请日：2011-06-15
申请人： Chaohui Liu , Chuan Zhou , Yi Liu , Qi Kang , Jun You , Kun Zhou
发明人： Chaohui Liu , Chuan Zhou , Yi Liu , Qi Kang , Jun You , Kun Zhou
IPC分类号： F26B3/347
CPC分类号： F26B3/347 , F26B5/042 , F26B5/048 , F26B5/06
摘要： A continuous microwave freeze-drying device comprises a vacuum water-trapping system (1), a microwave shield plate (2), a microwave bin (6) and a freeze-drying bin (5) located in the microwave bin (6), wherein the freeze-drying bin (5) comprises an upper bin opening, a left bin wall, a right bin wall and a bottom bin wall, and the left, right and bottom bin walls are all made from nonmetal wave transmitting materials, such as polyfluortetraethylene, polyethylene, polypropylene or quartz glass. The device solves the technical problem of freeze-drying failure caused by glow discharge of microwave under freeze-drying environment.
摘要翻译：连续微波冷冻干燥装置包括位于微波炉（6）中的真空吸水系统（1），微波屏蔽板（2），微波炉（6）和冷冻干燥箱（5）其特征在于，所述冷冻干燥箱（5）包括上部箱体开口，左侧箱壁，右侧箱壁和底部箱体壁，左侧和右侧箱体壁全部由非金属波浪传输材料制成，例如聚四氟乙烯，聚乙烯，聚丙烯或石英玻璃。该装置解决了冷冻干燥环境下微波辉光放电引起的冷冻干燥故障的技术问题。

2. 发明授权

US09568243B2 Continuous microwave freeze-drying device 有权
标题翻译：连续微波冷冻干燥装置
公开(公告)号：US09568243B2
公开(公告)日：2017-02-14
申请号：US13990767
申请日：2011-06-15
申请人： Chaohui Liu , Chuan Zhou , Yi Liu , Qi Kang , Jun You , Kun Zhou
发明人： Chaohui Liu , Chuan Zhou , Yi Liu , Qi Kang , Jun You , Kun Zhou
IPC分类号： F26B3/347 , F26B5/06 , F26B5/04
CPC分类号： F26B3/347 , F26B5/042 , F26B5/048 , F26B5/06
摘要： A continuous microwave freeze-drying device comprises a vacuum water-trapping system (1), a microwave shield plate (2), a microwave bin (6) and a freeze-drying bin (5) located in the microwave bin (6), wherein the freeze-drying bin (5) comprises an upper bin opening, a left bin wall, a right bin wall and a bottom bin wall, and the left, right and bottom bin walls are all made from nonmetal wave transmitting materials, such as polyfluortetraethylene, polyethylene, polypropylene or quartz glass. The device solves the technical problem of freeze-drying failure caused by glow discharge of microwave under freeze-drying environment.
摘要翻译：连续的微波冷冻干燥装置包括位于微波炉（6）中的真空吸水系统（1），微波屏蔽板（2），微波炉（6）和冷冻干燥箱（5）其特征在于，所述冷冻干燥箱（5）包括上部箱体开口，左侧箱壁，右侧箱壁和底部箱体壁，左侧和右侧箱体壁全部由非金属波浪传输材料制成，例如聚四氟乙烯，聚乙烯，聚丙烯或石英玻璃。该装置解决了冷冻干燥环境下微波辉光放电引起的冷冻干燥故障的技术问题。

3. 发明申请

US20090252395A1 System and Method of Identifying a Potential Lung Nodule 审中-公开
标题翻译：识别潜在肺结节的系统和方法
公开(公告)号：US20090252395A1
公开(公告)日：2009-10-08
申请号：US12484941
申请日：2009-06-15
申请人： Heang-Ping Chan , Berkman Sahiner , Lubomir M. Hadjiyski , Chuan Zhou , Nicholas Petrick
发明人： Heang-Ping Chan , Berkman Sahiner , Lubomir M. Hadjiyski , Chuan Zhou , Nicholas Petrick
IPC分类号： G06K9/00
CPC分类号： G06T7/0012 , A61B6/03 , A61B6/466 , A61B6/583 , G06T2207/10081 , G06T2207/30061
摘要： A computer assisted method of detecting and classifying lung nodules within a set of CT images to identify the regions of the CT images in which to search for potential lung nodules. The lungs are processed to identify a subregion of a lung on a CT image. The computer defines a nodule centroid for a nodule class of pixels and a background centroid for a background class of pixels within the subregion in the CT image; and determines a nodule distance between a pixel and the nodule centroid and a background distance between the pixel and the background centroid. Thereafter, the computer assigns the pixel to the nodule class or to the background class based on the first and second distances; stores the identification in a memory; and analyzes the nodule class to determine the likelihood of each pixel cluster being a true nodule.
摘要翻译：一种在一组CT图像内检测和分类肺结节的计算机辅助方法，以识别在其中搜索潜在肺结节的CT图像的区域。处理肺以识别CT图像上的肺的亚区域。计算机为CT图像中的子区域内的像素的背景类别定义了结节类像素的结节重心和背景质心; 并确定像素与结节重心之间的结节距离以及像素与背景质心之间的背景距离。此后，计算机基于第一和第二距离将像素分配给结节类或背景类; 将识别存储在存储器中; 并分析结节类以确定每个像素簇是真实结节的可能性。

4. 发明申请

US20050207630A1 Lung nodule detection and classification 审中-公开
标题翻译：肺结核检测和分类
公开(公告)号：US20050207630A1
公开(公告)日：2005-09-22
申请号：US10504197
申请日：2003-02-14
申请人： Heang-Ping Chan , Berkman Sahiner , Lubomir Hadjiyski , Chuan Zhou , Nicholas Petrick
发明人： Heang-Ping Chan , Berkman Sahiner , Lubomir Hadjiyski , Chuan Zhou , Nicholas Petrick
IPC分类号： A61B6/03 , G06F19/00 , G06K9/00 , G06T7/00
CPC分类号： G06T7/0012 , A61B6/03 , A61B6/466 , A61B6/583 , G06T2207/10081 , G06T2207/30061
摘要： A computer assisted method of detecting and classifying lung nodules within a set of CT images includes performing body contour, airway, lung and esophagus segmentation to identify the regions of the CT images in which to search for potential lung nodules. The lungs are processed to identify the left and right sides of the lungs and each side of the lung is divided into subregions including upper, middle and lower subregions and central, intermediate and peripheral subregions. The computer analyzes each of the lung regions to detect and identify a three-dimensional vessel tree representing the blood vessels at or near the mediastinum. The computer then detects objects that are attached to the lung wall or to the vessel tree to assure that these objects are not eliminated from consideration as potential nodules. Thereafter, the computer performs a pixel similarity analysis on the appropriate regions within the CT images to detect potential nodules and performs one or more expert analysis techniques using the features of the potential nodules to determine whether each of the potential nodules is or is not a lung nodule. Thereafter, the computer uses further features, such as speculation features, growth features, etc. in one or more expert analysis techniques to classify each detected nodule as being either benign or malignant. The computer then displays the detection and classification results to the radiologist to assist the radiologist in interpreting the CT exam for the patient.
摘要翻译：在一组CT图像中检测和分类肺结节的计算机辅助方法包括执行身体轮廓，气道，肺和食管分割，以识别CT图像的搜索潜在肺结节的区域。处理肺以识别肺的左侧和右侧，并且将肺的每一侧分为包括上部，中部和下部亚区域以及中央，中间和周边子区域的子区域。计算机分析每个肺部区域以检测和识别表示纵隔处或附近的血管的三维血管。然后，计算机检测附着到肺壁或血管树上的物体，以确保这些物体不被考虑为潜在的结节。此后，计算机对CT图像内的适当区域进行像素相似性分析以检测潜在的结节，并使用潜在结节的特征来执行一个或多个专家分析技术，以确定每个潜在结节是否为肺结核。此后，计算机在一个或多个专家分析技术中使用进一步的特征，例如推测特征，生长特征等，以将每个检测到的结节分类为良性或恶性。然后，计算机将检测和分类结果显示给放射科医师，以协助放射科医师解释患者的CT检查。

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