Abstract: Systems and techniques that facilitate automated localization of large vessel occlusions are provided. In various embodiments, an input component can receive computed tomography angiogram (CTA) images of a patient's brain. In various embodiments, a localization component can determine, via a machine learning algorithm, a location of a large vessel occlusion (LVO) in the patient's brain based on the CTA images. In various instances, the location of the LVO can comprise a laterality and an occlusion site. In various aspects, the laterality can indicate a right side or a left side of the patient's brain, and the occlusion site can indicate an internal carotid artery (ICA), an M1 segment of a middle cerebral artery (MCA) or an M2 segment of an MCA. In various cases, a visualization component can generate and display to a user a three-dimensional maximum intensity projection (MIP) reconstruction of the patient's brain based on the CTA images to facilitate visual verification of the LVO by the user.

Abstract: Systems and methods for rapid, accurate, fully-automated, brain hemorrhage deep learning (DL) based assessment tools are provided, to assist clinicians in the detection & characterization of hemorrhages or bleeds. Images may be acquired from a subject using an imaging source, and preprocessed to cleanup, reformat, and perform any needed interpolation prior to being analyzed by an artificial intelligence network, such as a convolutional neural network (CNN). The artificial intelligence network identifies and labels regions of interest in the image, such as identifying any hemorrhages or bleeds. An output for a user may also include a confidence value associated with the identification.

Abstract: Systems and techniques for generating and/or employing a computed tomography (CT) medical imaging stroke model are presented. In one example, a system employs a convolutional neural network to generate learned medical imaging stroke data regarding a brain anatomical region based on CT data associated with the brain anatomical region and diffusion-weighted imaging (DWI) data associated with one or more segmentation masks for the brain anatomical region. The system also detects presence or absence of a medical stroke condition in a CT image based on the learned medical imaging stroke data.

Abstract: Systems and techniques that facilitate automated localization of large vessel occlusions are provided. In various embodiments, an input component can receive computed tomography angiogram (CTA) images of a patient's brain. In various embodiments, a localization component can determine, via a machine learning algorithm, a location of a large vessel occlusion (LVO) in the patient's brain based on the CTA images. In various instances, the location of the LVO can comprise a laterality and an occlusion site. In various aspects, the laterality can indicate a right side or a left side of the patient's brain, and the occlusion site can indicate an internal carotid artery (ICA), an M1 segment of a middle cerebral artery (MCA) or an M2 segment of an MCA. In various cases, a visualization component can generate and display to a user a three-dimensional maximum intensity projection (MIP) reconstruction of the patient's brain based on the CTA images to facilitate visual verification of the LVO by the user.

Abstract: Systems and techniques for generating and/or employing a computed tomography (CT) medical imaging stroke model are presented. In one example, a system employs a convolutional neural network to generate learned medical imaging stroke data regarding a brain anatomical region based on CT data associated with the brain anatomical region and diffusion-weighted imaging (DWI) data associated with one or more segmentation masks for the brain anatomical region. The system also detects presence or absence of a medical stroke condition in a CT image based on the learned medical imaging stroke data.

Abstract: Systems and methods for rapid, accurate, fully-automated, brain hemorrhage deep learning (DL) based assessment tools are provided, to assist clinicians in the detection & characterization of hemorrhages or bleeds. Images may be acquired from a subject using an imaging source, and preprocessed to cleanup, reformat, and perform any needed interpolation prior to being analyzed by an artificial intelligence network, such as a convolutional neural network (CNN). The artificial intelligence network identifies and labels regions of interest in the image, such as identifying any hemorrhages or bleeds. An output for a user may also include a confidence value associated with the identification.

Abstract: A method and systems for analyzing medical imaging using machine learning are provided. In some aspects, the method includes using an input on the computing device to receive image data acquired from a subject, wherein the image data is in a raw data domain, applying, using the computing device, a trained machine learning algorithm to the image data, wherein the trained machine learning algorithm is configured to perform a predetermined analysis on the image data. The method also includes generating a report indicative of the predetermined analysis using the computing device.

Abstract: A measurement while drilling (MWD) system for use in a drilling string, the MWD system comprises: a resistivity module that is configured to generate resistivity information about a resistivity of a formation that is drilled by the drilling string; a near bit sub that is configured to generate inclination information about an inclination of a drill bit of the drilling string; a MWD module; a first wireless communication module that is configured to wirelessly send the resistivity information from the resistivity module to the MWD module; a second wireless communication module that is configured to wirelessly send inclination information from the near bit sub module to the MWD module; and wherein the MWD module is configured to participate in a transmission of the inclination information and the resistivity information towards an upper surface of the formation.

Abstract: An optical inspection system, the system includes: (i) an image sensor; and (ii) a single optical element, that at least partially surrounds an edge of an inspected object; wherein the optical element is adapted to direct light from different areas of the edge of the inspected object towards the image sensor so that the image sensor concurrently obtains images of the different areas.

Abstract: A measurement while drilling (MWD) system for use in a drilling string, the MWD system comprises: a resistivity module that is configured to generate resistivity information about a resistivity of a formation that is drilled by the drilling string; a near bit sub that is configured to generate inclination information about an inclination of a drill bit of the drilling string; a MWD module; a first wireless communication module that is configured to wirelessly send the resistivity information from the resistivity module to the MWD module; a second wireless communication module that is configured to wirelessly send inclination information from the near bit sub module to the MWD module; and wherein the MWD module is configured to participate in a transmission of the inclination information and the resistivity information towards an upper surface of the formation.

Abstract: A method, system and a computer program product for evaluating contact elements, the method includes: acquiring images of multiple groups of contact elements, wherein each group of contact element was expected to be contacted during a test by the same group of probes so as to form multiple probe marks; and evaluating at least one characteristic of a first contact element in response to a comparison between a number of potential probe marks that appear in the image of a first contact element and a number of potential probe marks that appear in an image of a second contact element.

Abstract: Method and inspection system. The inspection system includes: (i) a stage, for supporting an inspected object and for moving the inspected object by a movement that is characterized by speed variations; (ii) a signal generator, for generating triggering pulses at a fixed frequency regardless of the speed variations; (iii) a stage location generator, for providing location information indicative of a location of the stage at points of time that are determined by the triggering pulses; (iv) a strobe illuminator for illuminating areas of the inspected object in response to the triggering pulses; (v) a camera for acquiring images of areas of the inspected object in response to the triggering pulses; wherein overlaps between the images of the areas of the inspected object are characterized by overlap variations; and (vi) a processor for associating location information to the acquired images.

Abstract: A system and a method for method for printing a solder mask on a printed circuit board (PCB), the method includes: acquiring images of multiple areas of a PCB by an inspection unit while the PCB is supported by a mechanical stage; determining spatial differences between a model of the PCB and the PCB based on the images; determining solder mask ink deposition locations based on (i) the spatial differences, and (ii) locations of the model of the PCB that should be coated with the solder mask ink; and printing solder mask ink on the solder mask deposition locations by a printing unit, while the PCB is supported by the mechanical stage.

Abstract: An optical inspection system, the system includes: (i) an image sensor; and (ii) a single optical element, that at least partially surrounds an edge of an inspected object; wherein the optical element is adapted to direct light from different areas of the edge of the inspected object towards the image sensor so that the image sensor concurrently obtains images of the different areas.

Abstract: An optical inspection system, the system includes: (i) an image sensor; and (ii) a single optical element, that at least partially surrounds an edge of an inspected object; wherein the optical element is adapted to direct light from different areas of the edge of the inspected object towards the image sensor so that the image sensor concurrently obtains images of the different areas.

Abstract: A method, system and a computer program product for evaluating contact elements, the method includes: acquiring images of multiple groups of contact elements, wherein each group of contact element was expected to be contacted during a test by the same group of probes so as to form multiple probe marks; and evaluating at least one characteristic of a first contact element in response to a comparison between a number of potential probe marks that appear in the image of a first contact element and a number of potential probe marks that appear in an image of a second contact element.

Abstract: Method and inspection system. The inspection system includes: (i) a stage, for supporting an inspected object and for moving the inspected object by a movement that is characterized by speed variations; (ii) a signal generator, for generating triggering pulses at a fixed frequency regardless of the speed variations; (iii) a stage location generator, for providing location information indicative of a location of the stage at points of time that are determined by the triggering pulses; (iv) a strobe illuminator for illuminating areas of the inspected object in response to the triggering pulses; (v) a camera for acquiring images of areas of the inspected object in response to the triggering pulses; wherein overlaps between the images of the areas of the inspected object are characterized by overlap variations; and (vi) a processor for associating location information to the acquired images.

Abstract: A system and method for evaluating a criticality of a defect. The method may include: obtaining information indicative of at least one spatial relationship between at least one inspected pattern of a layer of a micro-electronic device and an inspected defect; and determining a criticality of the detected defect in response to the obtained information and in response to at least one rule that associates between a criticality of a defect and a spatial relationship between the defect and at least one edge of at least one pattern of a layer of a micro-electronic device.