Abstract: A mechanism for generating a set of imaging parameters used to reconstruct medical imaging data from raw or partially-processed medical imaging data. In an inner loop, the imaging parameter(s) are modified using one or more first image metrics produced using a no-reference image quality metric technique on medical imaging data produced using the imaging parameter(s). In an outer loop, the imaging parameter(s) are modified using one or more second image metrics produced using a full-reference image quality metric technique on comparison medical imaging data. The comparison medical imaging data is produced by processing raw or partially-processed reference medical imaging data using the imaging parameter(s).

Abstract: A mechanism for defining a set of preset parameter values for an ultrasound imaging system. Information about local machine-learning models, generated by a plurality of ultrasound imaging systems and updated responsive to operator feedback, is provided to an external server. The external server generates a global machine-learning model based on this information, which is then used to update the local machine-learning model on target ultrasound imaging systems.

Abstract: A mechanism for automatically generating and ranking M-mode lines for generating or defining M-mode data usable to assess fetal heart activity, e.g. determine a fetal heart rate. A region of interest, containing a fetal heart, in a sequence of ultrasound images is identified. The region of interest is used to define the position of each of a plurality of M-mode lines, e.g. anatomical M-mode lines. A quality measure of each M-mode line is determined based on M-mode data generated for each M-mode line, and the quality measures are then used to rank the M-mode lines.

Abstract: The present disclosure relates to the treatment of agitation caused by noradrenergic hyperarousal in an agitated subject. The present disclosure provides oromucosal dosage forms comprising effective amounts of latrepirdine either alone or in combination with dexmedetomidine or pharmaceutically acceptable salts thereof and one or more pharmaceutically acceptable carriers and/excipients. Methods of their use are also provided. The present disclosure also provides a method of treating depression by administering oromucosally a therapeutically effective amount of dexmedetomidine alone or in combination with latrepirdine.

Abstract: A mechanism for automatically generating and ranking M-mode lines for generating or defining M-mode data usable to assess fetal heart activity, e.g. determine a fetal heart rate. A region of interest, containing a fetal heart, in a sequence of ultrasound images is identified. The region of interest is used to define the position of each of a plurality of M-mode lines, e.g. anatomical M-mode lines. A quality measure of each M-mode line is determined based on M-mode data generated for each M-mode line, and the quality measures are then used to rank the M-mode lines.

Abstract: The invention relates to a computer-implemented method for automatically detecting anatomical structures (3) in a medical image (1) of a subject, the method comprising applying an object detector function (4) to the medical image, wherein the object detector function performs the steps of: (A) applying a first neural network (40) to the medical image, wherein the first neural network is trained to detect a first plurality of classes of larger-sized anatomical structures (3a), thereby generating as output the coordinates of at least one first bounding box (51) and the confidence score of it containing a larger-sized anatomical structure; (B) cropping (42) the medical image to the first bounding box, thereby generating a cropped image (11) containing the image content within the first bounding box (51); and (C) applying a second neural network (44) to the cropped medical image, wherein the second neural network is trained to detect at least one second class of smaller-sized anatomical structures (3b), thereby g

Abstract: A computer-implemented method for visualization of an elongated anatomical structure (20), for example of a fetal spine using ultrasound is provided.

Abstract: A mechanism for defining a set of preset parameter values for an ultrasound imaging system. Information about local machine-learning models, generated by a plurality of ultrasound imaging systems and updated responsive to operator feedback, is provided to an external server. The external server generates a global machine-learning model based on this information, which is then used to update the local machine-learning model on target ultrasound imaging systems.

Abstract: The invention provides for a method of obtaining a composite 3D ultrasound image of a region of interest. The method includes obtaining preliminary ultrasound data from a region of interest of a subject and identifying an anatomical feature within the region of interest based on the preliminary ultrasound data. A first imaging position and one or more additional imaging positions are then determined based on the anatomical feature. A first 3D ultrasound image is obtained from the first imaging position and one or more additional 3D ultrasound images are obtained from the one or more additional imaging positions, wherein a portion of the first 3D ultrasound image overlaps a portion of the one or more additional 3D ultrasound images, thereby forming an overlapping portion comprising the anatomical feature.

Abstract: The present disclosure relates to the treatment of agitation caused by noradrenergic hyperarousal in an agitated subject. The present disclosure provides oromucosal dosage forms comprising effective amounts of latrepirdine either alone or in combination with dexmedetomidine or pharmaceutically acceptable salts thereof and one or more pharmaceutically acceptable carriers and/excipients. Methods of their use are also provided. The present disclosure also provides a method of treating depression by administering oromucosally a therapeutically effective amount of dexmedetomidine alone or in combination with latrepirdine.

Abstract: The present invention relates to a device (10) for detecting a misuse of a medical imaging system (20), comprising a data interface (12) for acquiring medical image data (24) and audit log data (26) from the medical imaging system (20); a processing unit (14) which is configured to configured to analyse the medical image data (24) to determine whether or not a part of a fetus is imaged in the medical image data (24), to compare the medical image data (24) and the audit log data (26) with each other, and to determine based on said comparison whether there is a mismatch between the medical image data (24) and the audit log data (26); and a feedback unit (16) which is configured to generate a misuse alert signal if a mismatch is detected by the processing unit (14).

Abstract: A computer-implemented method for visualization of an elongated anatomical structure (20), for example of a fetal spine using ultrasound is provided.

Abstract: The invention relates to a computer-implemented method for automatically detecting anatomical structures (3) in a medical image (1) of a subject, the method comprising applying an object detector function (4) to the medical image, wherein the object detector function performs the steps of: (A) applying a first neural network (40) to the medical image, wherein the first neural network is trained to detect a first plurality of classes of larger-sized anatomical structures (3a), thereby generating as output the coordinates of at least one first bounding box (51) and the confidence score of it containing a larger-sized anatomical structure; (B) cropping (42) the medical image to the first bounding box, thereby generating a cropped image (11) containing the image content within the first bounding box (51); and (C) applying a second neural network (44) to the cropped medical image, wherein the second neural network is trained to detect at least one second class of smaller-sized anatomical structures (3b), thereby g

Abstract: The present invention relates to a device (2) and a method (100) for determining at least one final two-dimensional image or slice for visualizing an object of interest in a three-dimensional ultrasound volume.

Abstract: Disclosed in the present disclosure is a method, system and apparatus for prediction, estimation and prevention of occurrence of agitation episode in a subject predisposed to agitation. The method comprises receiving, from a first monitoring device attached to a subject, physiological data of sympathetic nervous system activity in the subject and activity data of the subject; receiving, from a computing device, a plurality of indications associated with a plurality of agitation episodes of the subject; analyzing, using at least one machine learning model, the physiological data, the activity data, and the plurality of indications to determine a probability of an occurrence of an agitation episode of the subject; and sending a signal to a second monitoring device to notify the second monitoring device of the probability of the occurrence of the agitation episode of the subject such that treatment can be provided to the subject to decrease sympathetic nervous system activity in the subject.

Abstract: In some embodiments, a method includes receiving first physiological data of sympathetic nervous system activity and establishing a baseline value of at least one physiological parameter by training at least one machine learning model using the first physiological data. The method further includes receiving, from a first monitoring device attached to a subject, second physiological data of sympathetic nervous system activity in the subject. Using the at least one machine learning model and based on the baseline value of at least one physiological parameter, the method includes analyzing the second physiological data to predict an agitation episode of the subject and sending a signal to a second monitoring device to notify of the prediction of the agitation episode of the subject such that treatment can be provided to the subject to decrease sympathetic nervous system activity in the subject.

Abstract: The invention provides for a method of obtaining a composite 3D ultrasound image of a region of interest. The method includes obtaining preliminary ultrasound data from a region of interest of a subject and identifying an anatomical feature within the region of interest based on the preliminary ultrasound data. A first imaging position and one or more additional imaging positions are then determined based on the anatomical feature. A first 3D ultrasound image is obtained from the first imaging position and one or more additional 3D ultrasound images are obtained from the one or more additional imaging positions, wherein a portion of the first 3D ultrasound image overlaps a portion of the one or more additional 3D ultrasound images, thereby forming an overlapping portion comprising the anatomical feature.

Abstract: The present invention relates to a device (2) and a method (100) for determining at least one final two-dimensional image or slice for visualizing an object of interest in a three-dimensional ultrasound volume.

Abstract: The present invention relates to a device (10) for detecting a misuse of a medical imaging system (20), comprising a data interface (12) for acquiring medical image data (24) and audit log data (26) from the medical imaging system (20); a processing unit (14) which is configured to configured to analyse the medical image data (24) to determine whether or not a part of a fetus is imaged in the medical image data (24), to compare the medical image data (24) and the audit log data (26) with each other, and to determine based on said comparison whether there is a mismatch between the medical image data (24) and the audit log data (26); and a feedback unit (16) which is configured to generate a misuse alert signal if a mismatch is detected by the processing unit (14).

Abstract: The invention relates to a method and an apparatus for cervical image analysis, wherein a transformation zone is identified in an acetic acid image by registering with its Lugol's iodine counterpart. Then, regions in the transformation zone which show significant changes in whiteness are identified as aceto-white regions and registered with the corresponding Lugol's iodine image, and it is determined if the identified regions in the Lugol's iodine image are iodine negative or positive. Based thereon, the aceto-white region can be categorized as one of metaplasia, inflammation or premalignant lesion region.