公开(公告)号：US20140377795A1

公开(公告)日：2014-12-25

申请号：US14367060

申请日：2012-12-19

Applicant: OPTICUL DIAGNOSTICS LTD. ,  OPTICUL DIAGNOSTICS Inc.

Inventor： Gallya Gannot ,  Dror Lederman ,  Moinuddin Hassan ,  Israel Gannot

IPC: C12Q1/04 ,  G01N21/65 ,  G01N21/25

CPC classification number: C12Q1/04 ,  C12M41/36 ,  G01N21/255 ,  G01N21/3577 ,  G01N21/39 ,  G01N21/64 ,  G01N21/65 ,  G01N2021/1742 ,  G01N2021/1744 ,  G01N2021/3595 ,  G01N2021/6417 ,  G01N2201/06113 ,  G01N2201/129 ,  G01N2201/1296 ,  G06F19/10

Abstract: A spectroscopic method for spectroscopic detection and identification of bacteria in culture is disclosed. The method incorporates construction of at least one data set, which may be a spectrum, interference pattern, or scattering pattern, from a cultured sample suspected of containing said bacteria. The data set is corrected for the presence of water in the sample, spectral features are extracted using a principal components analysis, and the features are classified using a learning algorithm. In some embodiments of the invention, for example, to differentiate MRSA from MSSA, a multimodal analysis is performed in which identification of the bacteria is made based on a spectrum of the sample, an interference pattern used to determine cell wall thickness, and a scattering pattern used to determine cell wall roughness. An apparatus for performing the method is also disclosed, one embodiment of which incorporates a multiple sample analyzer.

Abstract translation: 公开了用于光谱检测和鉴定培养细菌的光谱方法。 该方法包括来自怀疑含有所述细菌的培养样品的至少一个数据集的构建，其可以是光谱，干涉图案或散射图案。 对样品中水的存在进行数据集的校正，使用主成分分析提取光谱特征，并使用学习算法对特征进行分类。 在本发明的一些实施方案中，例如为了区分MRSA和MSSA，进行多模态分析，其中基于样品的光谱，用于确定细胞壁厚度的干涉图案和散射来确定细菌的鉴定 用于确定细胞壁粗糙度的图案。 还公开了一种用于执行该方法的装置，其一个实施例包括多个样本分析器。

公开(公告)号：US09365883B2

公开(公告)日：2016-06-14

申请号：US14367060

申请日：2012-12-19

Applicant: OPTICUL DIAGNOSTICS LTD. ,  OPTICUL DIAGNOSTICS Inc.

Inventor： Gallya Gannot ,  Dror Lederman ,  Hassan Moinuddin ,  Israel Gannot

IPC: G01N21/00 ,  C12Q1/04 ,  G01N21/65 ,  G01N21/3577 ,  G01N21/25 ,  C12M1/34 ,  G01N21/39 ,  G01N21/64 ,  G01N21/35 ,  G01N21/17 ,  G06F19/10

CPC classification number: C12Q1/04 ,  C12M41/36 ,  G01N21/255 ,  G01N21/3577 ,  G01N21/39 ,  G01N21/64 ,  G01N21/65 ,  G01N2021/1742 ,  G01N2021/1744 ,  G01N2021/3595 ,  G01N2021/6417 ,  G01N2201/06113 ,  G01N2201/129 ,  G01N2201/1296 ,  G06F19/10

Abstract: A spectroscopic method for spectroscopic detection and identification of bacteria in culture is disclosed. The method incorporates construction of at least one data set, which may be a spectrum, interference pattern, or scattering pattern, from a cultured sample suspected of containing said bacteria. The data set is corrected for the presence of water in the sample, spectral features are extracted using a principal components analysis, and the features are classified using a learning algorithm. In some embodiments of the invention, for example, to differentiate MRSA from MSSA, a multimodal analysis is performed in which identification of the bacteria is made based on a spectrum of the sample, an interference pattern used to determine cell wall thickness, and a scattering pattern used to determine cell wall roughness. An apparatus for performing the method is also disclosed, one embodiment of which incorporates a multiple sample analyzer.

Abstract translation: 公开了用于光谱检测和鉴定培养细菌的光谱方法。 该方法包括来自怀疑含有所述细菌的培养样品的至少一个数据集的构建，其可以是光谱，干涉图案或散射图案。 对样品中水的存在进行数据集的校正，使用主成分分析提取光谱特征，并使用学习算法对特征进行分类。 在本发明的一些实施方案中，例如为了区分MRSA和MSSA，进行多模态分析，其中基于样品的光谱，用于确定细胞壁厚度的干涉图案和散射来确定细菌的鉴定 用于确定细胞壁粗糙度的图案。 还公开了一种用于执行该方法的装置，其一个实施例包括多个样本分析器。

公开(公告)号：WO2010032245A3

公开(公告)日：2010-05-20

申请号：PCT/IL2009000908

申请日：2009-09-16

Applicant: OPTICUL DIAGNOSTICS LTD ,  BEN-DAVID MOSHE ,  GANNOT GALLYA ,  ERUV TOMER ,  MARKOWITZ ZVI

Inventor： BEN-DAVID MOSHE ,  GANNOT GALLYA ,  ERUV TOMER ,  MARKOWITZ ZVI

IPC: G06K9/00 ,  G01N33/50

CPC classification number: G06K9/00496

Abstract: This disclosure provides a method for detecting and/or identifying uncultured bacteria. The sample is an aerosol sample selected from a group consisting of cough, sneeze, saliva, mucus, bile, urine, vaginal secretions, middle ear aspirate, pus, pleural effusions, synovial fluid, abscesses, cavity swabs, serum, blood and spinal fluid. The method comprises obtaining absorption spectra (AS) of the sample, extracting and processing the acquired data, thereby detecting and/or identifying the bacteria.

Abstract translation: 本公开提供了用于检测和/或识别未培养的细菌的方法。 样品是选自咳嗽，打喷嚏，唾液，粘液，胆汁，尿液，阴道分泌物，中耳抽吸物，脓液，胸腔积液，滑液，脓肿，腔拭子，血清，血液和脊髓液的气溶胶样品 。 该方法包括获得样品的吸收光谱（AS），提取和处理所获取的数据，从而检测和/或识别细菌。

公开(公告)号：WO2008122975A3

公开(公告)日：2008-10-16

申请号：PCT/IL2008/000472

申请日：2008-04-06

Applicant: OPTICUL DIAGNOSTICS LTD. ,  BEN-DAVID, Moshe ,  GANNOT, Gallya ,  ERUV, Tomer

Inventor： BEN-DAVID, Moshe ,  GANNOT, Gallya ,  ERUV, Tomer

IPC: C12Q1/04

Abstract: The present invention provides a method for detecting and/or identifying specific bacteria within an uncultured sample. The method comprises steps selected inter alia from (a) obtaining an absorption spectrum (AS) of said uncultured sample; (b) acquiring the n dimensional volume boundaries for said specific bacteria; (c) data processing said AS; and, (d) detecting and/or identifying said specific bacteria if said m1 statistical correlation and/or said m features are within said n dimensional volume.

公开(公告)号：WO2010041251A3

公开(公告)日：2010-06-03

申请号：PCT/IL2009000960

申请日：2009-10-11

Applicant: OPTICUL DIAGNOSTICS LTD ,  BEN-DAVID MOSHE ,  GANNOT GALLYA ,  ERUV TOMER ,  MARKOWITZ ZVI

Inventor： BEN-DAVID MOSHE ,  GANNOT GALLYA ,  ERUV TOMER ,  MARKOWITZ ZVI

IPC: G06K9/00 ,  G01N33/50

CPC classification number: G06K9/00496

Abstract: The present invention provides a method for detecting and/or identifying specific bacteria within an uncultured sample, comprising steps of: a. obtaining an absorption spectrum (AS) of said uncultured sample; b. acquiring the n dimensional volume boundaries for said specific bacteria; c. data processing said AS; i. noise reducing; ii. extracting m features from said entire AS; iii. dividing said AS into several segments according to said m features; iv. calculating m 1 features of each of said segment; and, d. detecting and/or identifying said specific bacteria if said m 1 features and/or said m features are within said n dimensional volume; wherein said bacteria is a antibiotics resistance bacteria.

Abstract translation: 本发明提供了用于检测和/或鉴定未培养样品内的特定细菌的方法，包括以下步骤：a。 获得所述未培养样品的吸收光谱（AS） 湾 获取所述特定细菌的n维体积边界; C。 数据处理所述AS; 一世。 降噪; II。 从所述整个AS中提取m个特征; III。 根据所述m个特征将所述AS划分成若干段; IV。 计算每个所述片段的m 1个特征; 和，d。 如果所述m 1特征和/或所述m个特征在所述n维体积内，则检测和/或识别所述特定细菌; 其中所述细菌是抗生素抗性细菌。

公开(公告)号：WO2010032245A2

公开(公告)日：2010-03-25

申请号：PCT/IL2009/000908

申请日：2009-09-16

Applicant: OPTICUL DIAGNOSTICS LTD. ,  BEN-DAVID, Moshe ,  GANNOT, Gallya ,  ERUV, Tomer ,  MARKOWITZ, Zvi

Inventor： BEN-DAVID, Moshe ,  GANNOT, Gallya ,  ERUV, Tomer ,  MARKOWITZ, Zvi

IPC: G06K9/46

CPC classification number: G06K9/00496

Abstract: This disclosure provides a method for detecting and/or identifying uncultured bacteria. The sample is an aerosol sample selected from a group consisting of cough, sneeze, saliva, mucus, bile, urine, vaginal secretions, middle ear aspirate, pus, pleural effusions, synovial fluid, abscesses, cavity swabs, serum, blood and spinal fluid. The method comprises obtaining absorption spectra (AS) of the sample, extracting and processing the acquired data, thereby detecting and/or identifying the bacteria.

Abstract translation: 本公开提供了用于检测和/或鉴定未培养细菌的方法。 样品是选自咳嗽，打喷嚏，唾液，粘液，胆汁，尿液，阴道分泌物，中耳吸出物，脓液，胸腔积液，滑液，脓肿，腔拭子，血清，血液和脊髓液的气溶胶样品 。 该方法包括获得样品的吸收光谱（AS），提取和处理所获得的数据，从而检测和/或鉴定细菌。

公开(公告)号：WO2013093913A1

公开(公告)日：2013-06-27

申请号：PCT/IL2012/050534

申请日：2012-12-19

Applicant: OPTICUL DIAGNOSTICS LTD. ,  OPTICUL DIAGNOSTICS INC.

Inventor： GANNOT, Gallya ,  LEDERMAN, Dror ,  MOINUDDIN, Hassan ,  GANNOT, Israel

IPC: G01N21/00 ,  G01N21/25 ,  G01N33/00

CPC classification number: C12Q1/04 ,  C12M41/36 ,  G01N21/255 ,  G01N21/3577 ,  G01N21/39 ,  G01N21/64 ,  G01N21/65 ,  G01N2021/1742 ,  G01N2021/1744 ,  G01N2021/3595 ,  G01N2021/6417 ,  G01N2201/06113 ,  G01N2201/129 ,  G01N2201/1296 ,  G06F19/10

Abstract: A spectroscopic method for spectroscopic detection and identification of bacteria in culture is disclosed. The method incorporates construction of at least one data set, which may be a spectrum, interference pattern, or scattering pattern, from a cultured sample suspected of containing said bacteria. The data set is corrected for the presence of water in the sample, spectral features are extracted using a principal components analysis, and the features are classified using a learning algorithm. In some embodiments of the invention, for example, to differentiate MRS A from MSSA, a multimodal analysis is performed in which identification of the bacteria is made based on a spectrum of the sample, an interference pattern used to determine cell wall thickness, and a scattering pattern used to determine cell wall roughness. An apparatus for performing the method is also disclosed, one embodiment of which incorporates a multiple sample analyzer.

Abstract translation: 公开了用于光谱检测和鉴定培养细菌的光谱方法。 该方法包括来自怀疑含有所述细菌的培养样品的至少一个数据集的构建，其可以是光谱，干涉图案或散射图案。 对样品中水的存在进行数据集的校正，使用主成分分析提取光谱特征，并使用学习算法对特征进行分类。 在本发明的一些实施方案中，例如为了区分MRS A和MSSA，进行多模式分析，其中基于样品的光谱，用于确定细胞壁厚度的干涉图案和 用于确定细胞壁粗糙度的散射图。 还公开了一种用于执行该方法的装置，其一个实施例包括多个样本分析器。

公开(公告)号：WO2010076801A1

公开(公告)日：2010-07-08

申请号：PCT/IL2010/000008

申请日：2010-01-05

Applicant: OPTICUL DIAGNOSTICS LTD. ,  BEN-DAVID, Moshe ,  ERUV, Tomer ,  GANNOT, Gallya

Inventor： BEN-DAVID, Moshe ,  ERUV, Tomer ,  GANNOT, Gallya

IPC: G01N21/03 ,  G01N21/35

CPC classification number: G01N21/031 ,  G01N21/33 ,  G01N21/3581 ,  G01N21/359 ,  G01N2015/0088 ,  G01N2015/0693

Abstract: The present invention provides an optical unit (320) adapted to accommodate a sample and to enable optical detection of infection within said sample; said optical unit comprising a body (100); said body is characterized by a distal end and a proximal end interconnected via a main longitudinal axis; said body (100) comprising at least one mirror (50) coupled to said distal end; wherein said mirror (50) having a proximal and distal surfaces; said proximal surface faces said mask; said proximal surface is adapted to accommodate said sample.

Abstract translation: 本发明提供了一种光学单元（320），其适于容纳样品并且能够光学检测所述样品内的感染; 所述光学单元包括主体（100）; 所述主体的特征在于远端和通过主纵向轴线相互连接的近端; 所述主体（100）包括联接到所述远端的至少一个反射镜（50） 其中所述反射镜（50）具有近端和远端表面; 所述近端表面面对所述掩模; 所述近端表面适于容纳所述样品。

公开(公告)号：WO2010041251A2

公开(公告)日：2010-04-15

申请号：PCT/IL2009/000960

申请日：2009-10-11

Applicant: OPTICUL DIAGNOSTICS LTD. ,  BEN-DAVID, Moshe ,  GANNOT, Gallya ,  ERUV, Tomer ,  MARKOWITZ, Zvi

Inventor： BEN-DAVID, Moshe ,  GANNOT, Gallya ,  ERUV, Tomer ,  MARKOWITZ, Zvi

IPC: G06K9/00

CPC classification number: G06K9/00496

Abstract: The present invention provides a method for detecting and/or identifying specific bacteria within an uncultured sample, comprising steps of: a. obtaining an absorption spectrum (AS) of said uncultured sample; b. acquiring the n dimensional volume boundaries for said specific bacteria; c. data processing said AS; i. noise reducing; ii. extracting m features from said entire AS; iii. dividing said AS into several segments according to said m features; iv. calculating m 1 features of each of said segment; and, d. detecting and/or identifying said specific bacteria if said m 1 features and/or said m features are within said n dimensional volume; wherein said bacteria is a antibiotics resistance bacteria.

Abstract translation: 本发明提供了用于检测和/或鉴定未培养样品中的特定细菌的方法，包括以下步骤：a。 获得所述未培养样品的吸收光谱（AS）; 湾 获取所述特定细菌的n维体积边界; C。 数据处理表示AS; 一世。 降噪; II。 从整个AS中提取m个特征; III。 根据所述m个特征将所述AS划分成若干段; IV。 计算每个所述段的m 1个特征; 和，d。 如果所述m 1特征和/或所述m个特征在所述n维体积内，则检测和/或识别所述特定细菌; 其中所述细菌是抗生素抗性细菌。

公开(公告)号：CA2738813A1

公开(公告)日：2010-04-15

申请号：CA2738813

申请日：2009-10-11

Applicant: OPTICUL DIAGNOSTICS LTD

Inventor： BEN-DAVID MOSHE ,  GANNOT GALLYA ,  ERUV TOMER ,  MARKOWITZ ZVI

IPC: G06K9/00 ,  G01N33/50

Abstract: The present invention provides a method for detecting and/or identifying specific bacteria within an uncultured sample, comprising steps of: a. obtaining an absorption spectrum (AS) of said uncultured sample; b. acquiring the n dimensional volume boundaries for said specific bacteria; c. data processing said AS; i. noise reducing; ii. extracting m features from said entire AS; iii. dividing said AS into several segments according to said m features; iv. calculating m 1 features of each of said segment; and, d. detecting and/or identifying said specific bacteria if said m 1 features and/or said m features are within said n dimensional volume; wherein said bacteria is a antibiotics resistance bacteria.