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公开(公告)号:US20160350912A1
公开(公告)日:2016-12-01
申请号:US15117194
申请日:2015-02-02
申请人: HIROSHIMA UNIVERSITY
发明人: Tetsushi KOIDE , HoangAnh TUAN , Shigeto YOSHIDA , Tsubasa MISHIMA , Satoshi SHIGEMI , Toru TAMAKI , Tsubasa HIRAKAWA , Rie MIYAKI , Kouki SUGI
IPC分类号: G06T7/00
CPC分类号: G06T7/0012 , G02B23/2484 , G06T2207/10068
摘要: An endoscopic image diagnosis support system (100) includes: a memory (10) that stores learning images pre-classified into pathological types; and a processor (20) that, given an endoscopic image, performs feature value matching between an image of an identification target region in the endoscopic image and the learning images, to identify the pathological types in the identification target region. The processor (20) performs feature value matching between images of the identification target region and subdivided regions of the identification target region and the learning images to compute identification probabilities of the pathological types in the identification target region and the subdivided regions, and computes average values of the identification probabilities of the pathological types in the identification target region and the subdivided regions, the average values corresponding to identification probabilities of the pathological types in hierarchical overlap regions of the identification target region and the subdivided regions.
摘要翻译: 内窥镜图像诊断支持系统(100)包括:存储器(10),其存储预分类为病理类型的学习图像; 以及给予内窥镜图像的处理器(20)执行内窥镜图像中的识别对象区域的图像与学习图像之间的特征值匹配,以识别识别目标区域中的病理类型。 处理器(20)执行识别对象区域的图像与识别对象区域和学习图像的细分区域之间的特征值匹配,以计算识别目标区域和细分区域中的病理类型的识别概率,并计算平均值 识别目标区域和细分区域中的病理类型的识别概率的平均值对应于识别目标区域和细分区域的分层重叠区域中的病理类型的识别概率。
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公开(公告)号:US20160210520A1
公开(公告)日:2016-07-21
申请号:US15084457
申请日:2016-03-29
申请人: HIROSHIMA UNIVERSITY
CPC分类号: G06K9/00818 , G06K9/4642 , G06K9/4647 , G06K9/4652 , G06K9/52 , G06K2009/4666 , G06K2209/01 , G06T2207/20021
摘要: In a symbol recognition device, each histogram computation module receives an image of each partial region of a recognition target region in a binarized image and computes a frequency distribution of pixels of a given color in each line or column in the partial region; each run length determination module receives an image of each partial region of the recognition target region and determines whether or not a line or column of pixels of the given color having a certain length is present in the partial region; a control module feeds pixel information of the partial regions, read by scanning the binarized image stored in the image memory, into the histogram computation modules and the run length determination modules; a determination module determines a symbol included in the binarized image based on computation results of the histogram computation modules and determination results of the run length determination modules.
摘要翻译: 在符号识别装置中,每个直方图计算模块在二值化图像中接收识别目标区域的每个部分区域的图像,并且计算部分区域中每一行或列中给定颜色的像素的频率分布; 每个行程长度确定模块接收识别目标区域的每个部分区域的图像,并且确定在该部分区域中是否存在具有一定长度的给定颜色的一行或一列像素; 控制模块将通过扫描存储在图像存储器中的二值化图像读取的部分区域的像素信息馈送到直方图计算模块和游程长度确定模块; 确定模块基于直方图计算模块的计算结果和游程长度确定模块的确定结果来确定包含在二值化图像中的符号。
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公开(公告)号:US20230214970A1
公开(公告)日:2023-07-06
申请号:US18120366
申请日:2023-03-11
发明人: Tetsushi KOIDE , Michihiro HIDE , Yumi AOYAMA
CPC分类号: G06T5/20 , G06T7/11 , G06T5/50 , G06T7/0012 , A61B5/0077 , G06T2207/20021 , G06T2207/20212 , G06T2207/10056 , G06T2207/30088 , A61B5/442
摘要: Local image enhancement processing is executed on an image obtained by imaging a transcription material. The enhanced image is divided into a plurality of patch images and input to a machine learning identifier. The patch images after segmentation output from the machine learning identifier are combined to generate a likelihood map image of skin ridges from the whole image based on a result of the segmentation. Binarization processing is executed on the likelihood map image to generate a binary image. A skin ridge region is extracted based on the binary image to calculate the area of the skin ridge region.
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