Abstract: CEST imaging technique and MR scanning are used as an MRI method for measuring glutaminase mediated tumors. The method takes advantage of the fact that glutamine does not exhibit a significant Chemical Exchange Saturation Transfer (CEST) effect while glutamate does. In accordance with this method, one first obtains a glutamate CEST MRI map of the area of a tumor. L-glutamine (nontoxic up to several millimolar level) or glutaminase blocker is then injected and a post injection Glutamate CEST map is obtained. The difference in the spatial maps indicates the level of expression of glutaminase in the tumor.

Abstract: According to an example, an operation on a version of an electronic content may be performed and a determination as to whether the operation is an editing operation may be made. In response to the operation being an editing operation, a new version may be created and information pertaining to the performance of the operation on the new version may be recorded. In addition, for each significant version, information pertaining to the significant version may be displayed, in which the information may include an identification of the significant version, available operations on the significant version, and a last operation performed on the significant version, in which a significant version may include a version in which no editing operations have been applied or a version in which an operation that is visible to another user has been performed on the version and the operation is outstanding.

Abstract: CEST imaging technique and MR scanning are used as an MRI method for measuring glutaminase mediated tumors. The method takes advantage of the fact that glutamine does not exhibit a significant Chemical Exchange Saturation Transfer (CEST) effect while glutamate does. In accordance with this method, one first obtains a glutamate CEST MRI map of the area of a tumor. L-glutamine (nontoxic up to several millimolar level) or glutaminase blocker is then injected and a post injection Glutamate CEST map is obtained. The difference in the spatial maps indicates the level of expression of glutaminase in the tumor.

Abstract: An average size of a plurality of page images is determined, and a size of a first one of the page images is determined. The size of the first page image is compared to the average size. If the size of the first page image is larger than the average size by a first predetermined amount and larger than the average size by less than a second predetermined amount, then the first page image is rotated for printing. If the size of the first page image is larger than the average size by at least the second predetermined amount, then the first page images divided into multiple pages for printing.

Abstract: Data representing an image of text is received, as is data representing the text in non-image form. A valid content boundary within the image of the text is determined. For each character within the text in the non-image form, a location of the character within the image of the text is determined. Where the location of the character within the image of the text falls outside the valid content boundary, the character is removed from the data representing the text in the non-image form.

Abstract: An average size of a plurality of page images is determined, and a size of a first one of the page images is determined. The size of the first page image is compared to the average size. If the size of the first page image is larger than the average size by a first predetermined amount and larger than the average size by less than a second predetermined amount, then the first page image is rotated for printing. If the size of the first page image is larger than the average size by at least the second predetermined amount, then the first page image s divided into multiple pages for printing.

Abstract: Systems and methods for replacing non-image text are provided. One method for replacing non-image text includes padding a first data representing an image of text to create an image segment. The method includes replacing a second data representing non-image text with the image segment.

Abstract: In one embodiment, a digitized document, formatted as an image file and representing a scanned original page with a page boundary, is received. An image resolution for the digitized document is identified. A height and width of the page boundary, measured in pixels, is identified. A desired trim size for the digitized document is determined based on a function of the identified page boundary height and width and the image resolution. An available trim size that is closest to the desired trim size is selected for printing of the digitized document, via data indicative of available trim sizes stored in a computer-readable medium.

Abstract: Locations of word images corresponding to words in a document image are ascertained. The word images are grouped into clusters. For each of multiple of the clusters, a respective compressed word image cluster is determined based on a joint compression of respective ones of the word images that are grouped into the cluster. The positions of the word images in the document image are associated with the respective ones of the compressed word image clusters corresponding to the clusters respectively containing the word images.

Abstract: An image of a known text sample having a text type is generated. The image of the known text sample is input into each OCR engine of a number of OCR engines. Output text corresponding to the image of the known text sample is received from each OCR engine. For each OCR engine, the output text received from the OCR engine is compared with the known text sample, to determine a confidence value of the OCR engine for the text type of the known text sample.

Abstract: A page of a digitally scanned document and graphical user interface elements (GUI) are displayed. Each GUI element corresponds to a potential flaw within the page and includes an example image of the potential flaw. After the GUI elements are displayed, a user is permitted to select a user-detected flaw present within the page of the digitally scanned document by selecting one of the GUI elements.

Abstract: A system and method is disclosed for removing artifacts from a digitized document.

Abstract: Techniques for performing an incremental update to a set of hierarchically structured information that do not expose the structure and content of the hierarchically structured information to unauthorized parties. The present techniques include encrypting the hierarchically structured information such that an arrangement of nodes and corresponding data of the hierarchically structured information is not exposed and each node includes a corresponding node identifier that is not encrypted and updating the hierarchically structured information by referring to the nodes using the node identifiers.

Abstract: Illustrated is a system and method to prepare for display, within a Graphical User Interface (GUI), a subset selection pane, an icon and summary pane, and a sort pane. The system and method further to include to prepare for display, within the icon and summary pane, a result set that includes an icon representing a three dimensional book and a textual summary of the book. The system and method also includes enabling a screen object, within the subset selection pane, to receive input to select a subset of the result set to be displayed within the icon and summary pane. Further, the system and method includes enabling a screen object, within the sort pane, to receive input to select the subset of the result set to be sorted and displayed within the icon and summary pane.

Abstract: Systems and methods for replacing non-image text are provided. One method for replacing non-image text includes padding a first data representing an image of text to create an image segment. The method includes replacing a second data representing non-image text with the image segment.

Abstract: Data representing an image of text is received, as is data representing the text in non-image form. A valid content boundary within the image of the text is determined. For each character within the text in the non-image form, a location of the character within the image of the text is determined. Where the location of the character within the image of the text falls outside the valid content boundary, the character is removed from the data representing the text in the non-image form.

Abstract: The present disclosure provides a computer-implemented method of translating an image-based electronic document into a text-based electronic document. The method includes electronically scanning an image-based document to determine positions of word images in the image-based document. The method also includes extracting the word images from the image-based document and storing the word images to an electronic storage device. The method also includes grouping a subset of the word images into a word cluster based on a similarity of the word images, wherein the word images in the word cluster correspond to a same actual word. The method also includes generating a character-encoded transcription for the word cluster based on the word images in the word cluster. The method also includes adding the character-encoded transcription to a text-based electronic document at locations corresponding to the positions of the word images in the image-based document.

Abstract: In one embodiment, a digitized document, formatted as an image file and representing a scanned original page with a page boundary, is received. An image resolution for the digitized document is identified. A height and width of the page boundary, measured in pixels, is identified. A desired trim size for the digitized document is determined based on a function of the identified page boundary height and width and the image resolution. An available trim size that is closest to the desired trim size is selected for printing of the digitized document, via data indicative of available trim sizes stored in a computer-readable medium.

Abstract: An image of a known text sample having a text type is generated. The image of the known text sample is input into each OCR engine of a number of OCR engines. Output text corresponding to the image of the known text sample is received from each OCR engine. For each OCR engine, the output text received from the OCR engine is compared with the known text sample, to determine a confidence value of the OCR engine for the text type of the known text sample.

Abstract: First data represents an image of text including words. Second data represents the text in a non-image form. A particular word within the second data is replaced with a corresponding part of the first data representing the image of the particular word.