A method (and system) of segmenting one or more histological structures in a tissue image represented by multi-parameter cellular and sub-cellular imaging data includes receiving coarsest level image data for the tissue image, wherein the coarsest level image data corresponds to a coarsest level of a multiscale representation of first data corresponding to the multi-parameter cellular and sub-cellular imaging data. The method further includes breaking the coarsest level image data into a plurality of non-overlapping superpixels, assigning each superpixel a probability of belonging to the one or more histological structures using a number of pre-trained machine learning algorithms to create a probability map, extracting an estimate of a boundary for the: one or more histological structures by applying a contour algorithm to the probability map, and using the estimate of the boundary to generate a refined boundary for the one or more histological structures.

A method (and system) of segmenting one or more histological structures in a tissue image represented by multi-parameter cellular and sub-cellular imaging data includes receiving coarsest level image data for the tissue image, wherein the coarsest level image data corresponds to a coarsest level of a multiscale representation of first data corresponding to the multi-parameter cellular and sub-cellular imaging data. The method further includes breaking the coarsest level image data into a plurality of non-overlapping superpixels, assigning each superpixel a probability of belonging to the one or more histological structures using a number of pre-trained machine learning algorithms to create a probability map, extracting an estimate of a boundary for the: one or more histological structures by applying a contour algorithm to the probability map, and using the estimate of the boundary to generate a refined boundary for the one or more histological structures.

An image of a graphical user interface is captured. For example, a screen shot of a browser display is captured. Text syntax is executed that contains one or more parameters for identifying a graphical object. For example, the text syntax may identify a rectangle that contains the text “OK” where the text is red. Based on the text syntax, a graphical object is identified in the image of the graphical user interface. Information is returned that identifies how to access the graphical object in the graphical user interface. For example, coordinates of the graphical object are identified. This information can then be used in a test script using existing programming languages to test the graphical user interface. For example, the coordinates may be used to click on the OK button.

Quality associated with an interpretation of data captured as unstructured data can be determined. Attributes can be identified within the unstructured data automatically. Subsequently, sentiment associated with each of the attributes can be determined based on the unstructured data. Correctness of the unstructured data, and thus the interpretation, can be assessed based on a comparison of the attribute and associated sentiment with structured data. A quality score can be generated that captures the quality of the data interpretation in terms of correctness and as well as results of another analysis including completeness, among others. Comparison of the quality score to a threshold can dictate whether or not the interpretation is subject to further review.

Methods, systems, and computer-readable storage media for determining that a subject is a live person include obtaining a first image captured using a first camera disposed on a first side of a mobile device and obtaining a second image captured using a second camera disposed on a second side of the mobile device that is on the opposite side of the first side. The first image includes a representation of reflections visible on the corneas of a subject. The first image and the second image are pre-processing to generate a third image and a fourth image, respectively, where a first field of view represented in the third image at least partially overlaps with a second field of view of the fourth image. A determination is made, based on the third and fourth images, that a scene represented in the first field of view is substantially same as a scene represented in the second field of view. Responsive to determining that the scene represented in the first field of view is substantially same as the scene represented in the second field of view, identifying the subject as a live person.

Methods, systems, and computer-readable storage media for determining that a subject is a live person include obtaining a first image captured using a first camera disposed on a first side of a mobile device and obtaining a second image captured using a second camera disposed on a second side of the mobile device that is on the opposite side of the first side. The first image includes a representation of reflections visible on the corneas of a subject. The first image and the second image are pre-processing to generate a third image and a fourth image, respectively, where a first field of view represented in the third image at least partially overlaps with a second field of view of the fourth image. A determination is made, based on the third and fourth images, that a scene represented in the first field of view is substantially same as a scene represented in the second field of view. Responsive to determining that the scene represented in the first field of view is substantially same as the scene represented in the second field of view, identifying the subject as a live person.

A processor derives a first composition image representing a first composition included in a subject including three or more compositions from at least one radiation image acquired by imaging the subject, derives at least one removal radiation image obtained by removing the first composition from the at least one radiation image by using the first composition image, derives a plurality of other composition images representing a plurality of other compositions different from the first composition included in the subject by using the at least one removal radiation image, and derives a composite image obtained by synthesizing the first composition image and the plurality of other composition images at a predetermined ratio.

A processor derives a first composition image representing a first composition included in a subject including three or more compositions from at least one radiation image acquired by imaging the subject, derives at least one removal radiation image obtained by removing the first composition from the at least one radiation image by using the first composition image, derives a plurality of other composition images representing a plurality of other compositions different from the first composition included in the subject by using the at least one removal radiation image, and derives a composite image obtained by synthesizing the first composition image and the plurality of other composition images at a predetermined ratio.

An endoscope processor device generates first video signals. A recognition processing processor device generates second video signals by reflecting a result of recognition processing based on the first video signals. A display displays any one of the second video signals or the first video signals switched from the second video signals on the basis of first video switching signals from the recognition processing processor device. The display displays that a result display of the recognition processing is being stopped in a case where the result display of the recognition processing by the second video signals is stopped.

An endoscope processor device generates first video signals. A recognition processing processor device generates second video signals by reflecting a result of recognition processing based on the first video signals. A display displays any one of the second video signals or the first video signals switched from the second video signals on the basis of first video switching signals from the recognition processing processor device. The display displays that a result display of the recognition processing is being stopped in a case where the result display of the recognition processing by the second video signals is stopped.