Examples of the presently disclosed technology provide new systems and methods for real-time temperature propagation and tissue damage visualization during laser interstitial thermal therapy (LITT) procedures that do not rely on real-time MR imaging. Accordingly, examples enable performance of LITT procedures in regular operating rooms lacking MR-equipmentthereby reducing costs and improving availability for LITT procedures. Examples achieve these advantages by leveraging discretized patient-specific 3D brain structure representations to perform numerical methods for solving partial differential equations that estimate real-time (or close to real-time) temperature propagation within a patient's brain during a LITT procedure.

A system and method of extracting tables and figures from a drawing document is disclosed. The method may include processing coloured image to segmented binary image and extracting a plurality of horizontal lines and a plurality of vertical lines from a foreground of the image. The method may further include detecting a set of candidate table region from the plurality of horizontal lines and the plurality of vertical lines in the image. Further, the method may include calculating textual region density corresponding to each of the set of candidate table regions in the image. The method may further include identifying at least one relevant table region from the set of candidate table regions in the image and a text free region from the at least one additional region in the image. The method may further include identifying at least one figure region from the dilated text free region.

An online handwriting document layout analysis system includes a preprocess unit serving to receive a document composed of a plurality of strokes and to generate an undirected graph including a plurality of nodes and a plurality of edges for representing relations between different strokes. A bidirectional recursive neural network unit for initializing a feature vector of each of the nodes and initializing a feature vector of each of edges. A graphic neural network unit serves to update the feature vectors of the nodes and the edges for obtaining updated feature vectors. A fully connected neural network unit serves for performing a coarse-grained object classifying and a fine-grained object classifying for each of the nodes and the edges based on the updated feature vectors. A document restoration unit serves for restoring a tree structure of the document.

Presented herein are systems and methods for the employment of machine learning models for image processing. A mobile application for client-side image processing and validation, which interacts with and leverages native image processing software of the client device, where the image processing software and the mobile application include any number of machine-learning models for identifying a document and attributes of the document for recognition and validation. This mobile application uses the image processing software from a client operating system to control the camera. The image processing software generates various types of information about a video frame and the document, and the mobile application invokes APIs or software libraries of the image processing software to access the information and validate the frame and document.

An analog meter reading system is applied to an analog meter provided with a scale and a pointer and reads a measured value of the analog meter. The analog meter reading system includes: a unique information acquisition unit that acquires unique information of the analog meter; an image acquisition unit that acquires an image of the analog meter for reading the measured value; a detection unit that detects a reference point on the scale and a pointer from the image; a rotation angle calculation unit that calculates a rotation angle of the pointer until a state in which the pointer points to the reference point changes to a state in which the pointer points to the measuring point based on the reference point and the pointer that are detected; and a measured value conversion unit that converts the rotation angle into the measured value using the unique information.

The disclosure includes a system and method for determining a first measure of blur value associated with a first portion of a document under test; determining a second measure of blur value associated with a second portion of the document under test; determining whether an inconsistency in a set measure of blur values associated with the document under test is present, wherein the set of measure of blur values associated with the document under test includes the first measure of blur value and the second measure of blur value; and modifying a likelihood that the document is accepted or rejected based on whether the inconsistency is absent or present, respectively.

A method and system of determining shape of a table in a document is disclosed. A region of interest (ROI) from a binarized image of the document is determined is detected corresponding to the table based on detection of a plurality of lines. The ROI is extracted based on a minimum height threshold and a minimum width threshold of the document image. A cluster of points corresponding to each corner of the ROI are determined based on a height of the ROI and contour detection. A corner type of each corner is determined to be one of a 10 pointed corner or a curved corner and in case the corner type of least two corners is determined as the curved corner the shape of the table is determined as a rounded corner structure.

According to one aspect, the subject matter described herein includes a method for extracting text from unstructured documents. The method includes receiving a page of an unstructured document; extracting, from the page, a glyph identifier and a glyph position for each glyph on the page; and generating an adjacency graph based on the glyph positions for each glyph on the page, each node in the graph corresponding to a glyph and comprising glyph information that includes at least the glyph identifier and the glyph position for the respective glyph. The method further includes processing the adjacency graph by a machine learning model to classify edges and nodes in the adjacency graph, then grouping the glyphs according to their edge and node classifications to produce text output.

The present invention addresses the use of an OCR and computer vision technique/technology that enhances optimization of processing and memory resources related to every OCR stage subsequent to Image Acquisition, utilizing adaptive thresholding to incorporate images (text, images, and video) through pre-processed reversed binarization (bitmapping and pixel-wise).

A method for text-image integration is provided. The method may include receiving a question related to pairable data comprising text data and image data. Embeddings are generated from the text tokens and image encodings. Embeddings are generated from the text tokens and image encodings. The embeddings include text embeddings and image embeddings. A spectral conversion of the text embeddings and the image embeddings is performed to generate spectral data. The spectral data is processed to extract text-image features. The text-image features are processed to generate inferred answers to the question.