Abstract: Computer-implemented methods and systems are provided for interpreting a whole-slide image of a tissue specimen. Such a method includes detecting biological entities in a region of interest independently at each magnification level in a whole-slide image. An entity graph is generated for each magnification level, the entity graph comprising nodes, representing respective biological entities detected at that magnification level, interconnected by edges representing interactions between entities. The method also includes, for each region of interest, generating a hierarchical graph, defining a hierarchy of the entity graphs for that region, in which nodes of different entity graphs are interconnected by hierarchical edges representing hierarchical relations between nodes of the entity graphs.

Abstract: Embodiments of the invention relate to a computer-implemented method for quantifying a biomarker in a tissue sample of an organism. An image analysis system receives images of a stained tissue sample. Each received digital image depicts the tissue sample region at the end of an exposure interval. The system analyzes the intensity values and exposure intervals of the received digital images for determining the time when the intensity values corresponding to the plurality of exposure intervals ordered according to ascending exposure interval lengths reach a plateau (saturation residence time—SRT). The system determines the amount of a biomarker in the tissue sample and/or predicts a tumor stage and/or a treatment recommendation as a function of the SRT.

Abstract: A system and process for extracting information from filled form images is described. In one example, the claimed invention first extracts textual information and the hierarchy in a blank form. This information is then used to extract and understand the content of filled forms. In this way, the system does not have to analyze from the beginning each filled form. The system is designed so that it remains as generic as possible. The number of hard-coded rules in the whole pipeline was minimized to offer an adaptive solution able to address the largest number of forms, with various structures and typography. The system is also created to be integrated as a built-in function in a larger pipeline. The form understanding pipeline could be the starting point of any advanced Natural Language Processing application.

Abstract: Computer-implemented methods and systems are provided for interpreting a whole-slide image of a tissue specimen. Such a method includes detecting biological entities in a region of interest independently at each magnification level in a whole-slide image. An entity graph is generated for each magnification level, the entity graph comprising nodes, representing respective biological entities detected at that magnification level, interconnected by edges representing interactions between entities. The method also includes, for each region of interest, generating a hierarchical graph, defining a hierarchy of the entity graphs for that region, in which nodes of different entity graphs are interconnected by hierarchical edges representing hierarchical relations between nodes of the entity graphs.

Abstract: A system and process for extracting information from filled form images is described. In one example, the claimed invention first extracts textual information and the hierarchy in a blank form. This information is then used to extract and understand the content of filled forms. In this way, the system does not have to analyze from the beginning each filled form. The system is designed so that it remains as generic as possible. The number of hard-coded rules in the whole pipeline was minimized to offer an adaptive solution able to address the largest number of forms, with various structures and typography. The system is also created to be integrated as a built-in function in a larger pipeline. The form understanding pipeline could be the starting point of any advanced Natural Language Processing application.

Abstract: A system and process for extracting information from filled form images is described. In one example the claimed invention first extracts textual information and the hierarchy in a blank form. This information is then used to extract and understand the content of filled forms. In this way, the system does not have to analyze from the beginning each filled form. The system is designed so that it remains as generic as possible. The number of hard coded rules in the whole pipeline was minimized to offer an adaptive solution able to address the largest number of forms, with various structures and typography. The system is also created to be integrated as a built-in function in a larger pipeline. The form understanding pipeline could be the starting point of any advanced Natural Language Processing application.

Abstract: Methods and systems are provided to extract information within complex documents, and the extracted information may be compared to identify differences between complex documents or the extracted information may be analyzed with respect to the individual document. Information is extracted from complex documents comprising unstructured data to create a structured data repository, or analytics knowledge base. This database may be utilized to compare concepts that are common to one or more documents, allowing ease of comparison of documents, and identification of information that is different or identification of (same or similar) information that is presented differently in a set of complex documents.

Abstract: Methods and systems are provided to extract information within complex documents, and the extracted information may be compared to identify differences between complex documents or the extracted information may be analyzed with respect to the individual document. Information is extracted from complex documents comprising unstructured data to create a structured data repository, or analytics knowledge base. This database may be utilized to compare concepts that are common to one or more documents, allowing ease of comparison of documents, and identification of information that is different or identification of (same or similar) information that is presented differently in a set of complex documents.

Abstract: A system and process for extracting information from filled form images is described. In one example the claimed invention first extracts textual information and the hierarchy in a blank form. This information is then used to extract and understand the content of filled forms. In this way, the system does not have to analyze from the beginning each filled form. The system is designed so that it remains as generic as possible. The number of hard coded rules in the whole pipeline was minimized to offer an adaptive solution able to address the largest number of forms, with various structures and typography. The system is also created to be integrated as a built-in function in a larger pipeline. The form understanding pipeline could be the starting point of any advanced Natural Language Processing application.

Abstract: Computer-implemented methods are provided for generating a data structure representing tabular information in a scanned image. Such a method can include storing image data representing a scanned image of a table, processing the image data to identify positions of characters and lines in the image, and mapping locations in the image of information cells, each containing a set of the characters, in dependence on said positions. The method can also include, for each cell, determining cell attribute values, dependent on the cell locations, for a predefined set of cell attributes, and supplying the attribute values as inputs to a machine-learning model trained to pre-classify cells as header cells or data cells in dependence on cell attribute values.

Abstract: A system and process for extracting information from filled form images is described. In one example the claimed invention first extracts textual information and the hierarchy in a blank form. This information is then used to extract and understand the content of filled forms. In this way, the system does not have to analyze from the beginning each filled form. The system is designed so that it remains as generic as possible. The number of hard coded rules in the whole pipeline was minimized to offer an adaptive solution able to address the largest number of forms, with various structures and typography. The system is also created to be integrated as a built-in function in a larger pipeline. The form understanding pipeline could be the starting point of any advanced Natural Language Processing application.

Abstract: A system and process for extracting information from filled form images is described. In one example the claimed invention first extracts textual information and the hierarchy in a blank form. This information is then used to extract and understand the content of filled forms. In this way, the system does not have to analyze from the beginning each filled form. The system is designed so that it remains as generic as possible. The number of hard coded rules in the whole pipeline was minimized to offer an adaptive solution able to address the largest number of forms, with various structures and typography. The system is also created to be integrated as a built-in function in a larger pipeline. The form understanding pipeline could be the starting point of any advanced Natural Language Processing application.

Abstract: Computer-implemented methods are provided for generating a data structure representing tabular information in a scanned image. Such a method can include storing image data representing a scanned image of a table, processing the image data to identify positions of characters and lines in the image, and mapping locations in the image of information cells, each containing a set of the characters, in dependence on said positions. The method can also include, for each cell, determining cell attribute values, dependent on the cell locations, for a predefined set of cell attributes, and supplying the attribute values as inputs to a machine-learning model trained to pre-classify cells as header cells or data cells in dependence on cell attribute values.

Abstract: A computer-implemented method for modifying patterns in datasets using a generative adversarial network may be provided. The method comprises providing pairs of data samples. The pairs comprise each a base data sample and a modified data sample. Thereby, the modified pattern is determined by applying random modifications to the base data sample. Additionally, the method comprises training of the generator for building a model of the generator using an adversarial training method and using the pairs of data samples as input, wherein the discriminator receives as input dataset pairs of datasets, the dataset pairs comprising each a prediction output of the generator based on a base data sample and the corresponding modified data sample, thereby optimizing a joint loss function for the generator and the discriminator, and predicting an output dataset for unknown data samples as input for the generator without the discriminator.

Abstract: A method of determining a hierarchy of a blank template using an image of the blank template and using the determined hierarchy for providing labels and field values of text lines of a filled form document.

Abstract: A system and process for extracting information from filled form images is described. In one example the claimed invention first extracts textual information and the hierarchy in a blank form. This information is then used to extract and understand the content of filled forms. In this way, the system does not have to analyze from the beginning each filled form. The system is designed so that it remains as generic as possible. The number of hard coded rules in the whole pipeline was minimized to offer an adaptive solution able to address the largest number of forms, with various structures and typography. The system is also created to be integrated as a built-in function in a larger pipeline. The form understanding pipeline could be the starting point of any advanced Natural Language Processing application.

Abstract: The invention relates to the automated determination of the staining quality of an IHC stained biological sample. A plurality of features is extracted from a digital IHC stained tissue image. The features are input into a first classifier configured to identify the extended tissue type of the depicted tissue as a function of the extracted features. An extended tissue type is a tissue type with a defined expression level of the tumor marker. In addition, the extracted features are input into a second classifier configured to identify a contrast level of the depicted tissue as a function of at least some second ones of the extracted features. The contrast level indicates the intensity contrast of pixels of the stained tissue. Then, a staining quality score of the image is computed as a function of the identified extended tissue type and the identified contrast level.

Abstract: The invention relates to a computer-implemented method for automatically extracting data from a digital image comprising a graphical representation of quantitative data. The method comprises: Basic graphical objects are detected and structural primitives determined comprising grouping the basic graphical objects based on geometric relations. A semantic label is assigned to each of the structural primitives. A spatial data region of the graphical representation is determined using the semantic labels of the structural primitives. Quantitative data values are extracted which are represented by structural primitives within the data region which are assigned with first semantic labels identifying the respective structural primitives to represent quantitative data. The extracted quantitative data values are provided in units of pixels according to an image coordinate system.

Abstract: A system and process r extracting information from filled form images is described. In one example the claimed invention first extracts textual information and the hierarchy in a blank form. This information is then used to extract and understand the content of filled forms. In this way, the system does not have to analyze from the beginning each filled form. The system is designed so that it remains as generic as possible. The number of hard coded rules in the whole pipeline was minimized to offer an adaptive solution able to address the largest number of forms, with various structures and typography. The system is also created to be integrated as a built-in function in a larger pipeline. The form understanding pipeline could be the starting point of any advanced Natural Language Processing application.

Abstract: A method of determining a hierarchy of a blank template using an image of the blank template and using the determined hierarchy for providing labels and field values of text lines of a filled form document.