Koninklijke Philips Corporation N.v.

Krishnamoorthy Palanisamy

Nagaraju Bussa

Vikram Basawaraj Patil Okaly

Ravindra Balasaheb Patil

Shriram Sethuraman

Rajendra Singh Sisodia

Ramon Quido Erkamp

John Petruzzello

Ajay Anand

Shiwei Zhou

Rithesh Sreenivasan

Shankar Mosur Venkatesan

Sushanth Govinahallisathyanarayana

Dinesh Mysore Siddu

Sergei Shulepov

Christopher Stephen Hall

Rick Bezemer

Oladimeji Feyisetan Farri

Nico Maris Adriaan De Wild

Frank Verbakel

Denny Mathew

Larry Nielsen

Sudipta Chaudhury

Rohan Joshi

Sabina Manzari

Anshul Jain

Pravin Pawar

Sushanth Govinahalli Sathyanarayana

A method for deriving one or more hemodynamic parameters based on blood-velocity and arterial diameter measures, each sampled recurrently or continuously over a time period to obtain for each a data series spanning a time window (i.e. a waveform). Additionally, a radial blood velocity profile is computed indicative of blood velocity as a function of radial position across a plane cut perpendicularly across the vessel lumen. This gives an indication of how blood velocity varies for the individual patient across the vessel diameter. This information supplements the standard blood-velocity and arterial diameter measures as inputs to a transfer function which maps the inputs to hemodynamic parameters.

Hemodynamic parameter estimation

A medical imaging system () includes a processor and memory with instructions executable by the processor to receive () three-dimensional medical image data () comprising multiple slices, receive () an imaging modality () of the three-dimensional medical image data, receive () an anatomical view classification () of the three-dimensional medical image data, select () a chosen abnormality detection module () from a set of abnormality detection modules () using the imaging modality and the anatomical view classification, wherein at least a portion of the abnormality detection modules is a convolution neural network trained for identifying if the at least a portion of the multiple slices as either normal or abnormal, classify () the at least a portion of the multiple slices as normal or abnormal using the abnormality detection module, and choose () a set of selected slices () from the multiple slices according to a predetermined selection criteria () if a predetermined number of the multiple slices are classified as abnormal.

Automatic slice selection in medical imaging

The invention provides a method for guiding the acquisition of ultrasound data. The method begins by obtaining ultrasound data from a plurality of data acquisition planes and performing spatial registration of the data acquisition planes. A number of vessels are then identified in each data acquisition plane. A location of a vessel bifurcation is then identified based on the spatial registration of the data acquisition planes and the number of vessels in each data acquisition plane. A guidance instruction is generated based on the location of the vessel bifurcation, wherein the guidance instruction is adapted to indicate a location to obtain further ultrasound data.

Systems and methods for guided ultrasound data acquisition

The invention relates to a system, an ultrasound probe and a corresponding method for measuring arterial parameters using non-imaging ultrasound. The system comprises an acquisition unit for acquiring doppler ultrasound signal from a blood vessel and a processing unit for processing the acquired doppler ultrasound signal and to determine the changes in the blood vessel through the measurements of at least Peak Systolic Velocity (PSV) and Pulse Wave Velocity (PWV). The acquisition unit comprises an ultrasound probe having a plurality of transducer elements arranged in a grid configuration, and comprising a first probe () and a second probe () detachably connected to each other. In the split configuration the ultrasound probe is provided to measure the PWV globally between the carotid and femoral arteries, or the PSV and PWV locally and simultaneously. In the integrated configuration the PSV or PWV may be measured locally.

Ultrasound probe, system and method for measuring arterial parameters using non-imaging ultrasound

Presented are concepts for detecting subject motion in medical imaging of a subject. One such concept obtains a motion classification model representing relationships between motion of image features and subject motion values. For each of a plurality of medical slice images of an imaged volume of the subject, an image feature of the medical slice image is extracted. Based on the extracted image feature for each of the plurality of medical slice images, motion information for the image feature is determined. Based on the motion information for the image feature and the obtained motion classification model, a subject motion value is determined.

Detecting subject motion in medical imaging

A device, system, and method is provided for detecting pain in a cardiac-related region of the body and determining whether that pain is cardiac or non-cardiac. The device, system, and method may include calculating or determining a first feature based on a variation in activity level and a variation in the detected heartrate measurement and a second feature based on a variation in the detected ECG features and a first feature and then subjecting at least the first feature and the second feature to a cardiac pain classifier to determine a cardiac classification.

Device, system, and method for detecting and determining cardiac and non-cardiac pain

Embodiments of present disclosure disclose method and system for generating a medical image based on a textual data in a medical report. For generation, a textual data from each of one or more medical reports of the patient is retrieved. The textual data comprises one or more medical events and corresponding one or more attributes associated with each of the one or more medical reports. Further, a matching score for each of plurality of reference images is computed based on the textual data, using a first machine learning model. Upon computing the matching score, one or more images are selected from the plurality of reference images based on the matching score associated with each of the plurality of reference images. The medical image for the patient is generated based on the one or more images and the textual data using a second machine learning model.

Method and system for generating medical image based on textual data in medical report

A method for aligning spatially different subvolumes of ultrasonic data of a blood vessel comprising: acquiring temporally discrete signals of a blood vessel with elements of a two dimensional array of ultrasonic transducer elements from spatially different depths of scanning opposed by each transducer element, said array being located in a first position with respect to the blood vessel during the acquiring; Doppler processing the temporally discrete signals received from each transducer element to produce spectral Doppler data of the scanning depth opposed by each transducer element; producing a first three dimensional map of the spectral Doppler data in spatial relationship to the position of the array with respect to the blood vessel; acquiring temporally discrete signals of the blood vessel with elements of the two dimensional array of ultrasonic transducer elements from spatially different depths of scanning opposed by each transducer element, said array being located in a second position with respect to the blood vessel during the acquiring; Doppler processing the temporally discrete signals received from each transducer element to produce spectral Doppler data of the scanning depth opposed by each transducer element; producing a second three dimensional map of the spectral Doppler data in spatial relationship to the position of the array with respect to the blood vessel; aligning the first three dimensional map with the second three dimensional map on the basis of one or more regions of matching spectral Doppler data of the two map; and producing a combined three dimension map of the blood flow of the vessel from the aligned first and second three dimensional maps.

Method for aligning spatially different subvolumes of ultrasonic data of a blood vessel

A central signal segregation station () employs a signal acquisition controller () and a signal segregation controller (). In operation, the signal acquisition controller () receives a plurality of different types of physiological signals from a plurality of unknown physiological sensors (). For a monitoring of the physiological signals, the signal segregation controller () identifies a particular type of each physiological signal based on distinct signal features of each physiological signal corresponding to a different physiological signal model () among a plurality of physiological signal models () derived from known types of physiological sensors. For analyzing the physiological signals, the station () may further employ a signal analyzing controller () executing signal quality processing of the physiological signals, providing signal-specific feedback to any physiological sensor(s) communicating low quality physiological signal(s), annotating specific regions of each physiological signal having maximum diagnostic information and/or performing a confirmatory diagnosis of the physiological signals.

Central signal segregation system

There is provided a computer-implemented method () for obscuring one or more facial features of a subject in an image. A head of the subject is detected in the image () and a location of one or more facial features of the subject is identified in the image (). A region of the image to modify is determined based on the location of the one or more facial features (). The determined region comprises a part of the head on which the one or more facial features are located. The image within the determined region is modified to obscure the one or more facial features ().

Obscuring facial features of a subject in an image

A non-imaging diagnostic ultrasound system for carotid artery diagnosis has a two dimensional array probe () with a low element count and relatively large element size which can cover an area of the carotid artery at its bifurcation. The elements are operated independently with no phasing, and detect Doppler flow spatially beneath each element. The system produces maps of carotid blood flow in two or three dimensions and can assemble an extended view of the flow by matching segments of the carotid flow as the probe is moved over the vessel. Once the carotid artery has been localized, the degree of stenosis is assessed by automated measurements of peak systolic velocity and blood flow turbulence.

System for automated screening of carotid stenosis

A diagnostic ultrasound system for carotid artery diagnosis has a two dimensional array probe with a low element count and relatively large element size which can cover an area of the carotid artery at its bifurcation. The elements are operated independently with no phasing, and detect Doppler flow spatially beneath each element. The system produces maps of carotid blood flow in two or three dimensions and can assemble an extended view of the flow by matching segments of the carotid flow as the probe is moved over the vessel. Once the carotid artery has been localized, the degree of stenosis is assessed by automated measurements of peak systolic velocity and blood flow turbulence.

Doppler ultrasound system for diagnosing carotid stenosis

The present invention relates to a method of automatic labeling of activity of a subject on ECG data. The method of the invention comprises acquiring at least one physiological input signal purporting to an ECG signal and processing thereof. The processing of the at least one physiological input signal comprises conditioning the ECG signal and processing thereof, wherein the processing comprises obtaining respiration data from the ECG signal, identifying the activity pertaining to the said ECG data based on at least a signal specific feature of the said ECG signal, wherein the respiration data are used for differentiating activities performed by the subject, and labeling the said ECG data with the said activity, automatically. The present invention also relates to a system for automatic labeling of activity on ECG data in accordance with the method of the invention.

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Bengaluru, India

Krishnamoorthy Palanisamy