公开(公告)号：US20210158526A1

公开(公告)日：2021-05-27

申请号：US17047102

申请日：2019-04-12

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Ravindra Balasaheb Patil ,  Rithesh Sreenivasan ,  Krishnamoorthy Palanisamy ,  Nagaraju Bussa

IPC: G06T7/00 ,  G06K9/62 ,  G16H30/20 ,  G16H50/20 ,  G16H30/40 ,  G16H40/20 ,  G16H40/67 ,  G06N3/08 ,  A61B5/055 ,  A61B6/00 ,  A61B8/08

Abstract: The invention provides for a medical imaging system (100, 300, 400, 700) comprising: a memory (110) for storing machine executable instructions (120) and a processor (106) for controlling the medical imaging system. Execution of the machine executable instructions causes the processor to: receive (200) three-dimensional medical image data (122) comprising multiple slices; receive (202) an imaging modality (124) of the three-dimensional medical image data; receive (204) an anatomical view classification (126) of the three-dimensional medical image data; select (206) a chosen abnormality detection module (130) from a set of abnormality detection modules (128) 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 (208) the at least a portion of the multiple slices as normal or abnormal using the abnormality detection module; and choose (210) a set of selected slices (136) from the multiple slices according to a predetermined selection criteria (134) if a predetermined number of the multiple slices are classified as abnormal.

公开(公告)号：US12165308B2

公开(公告)日：2024-12-10

申请号：US17047102

申请日：2019-04-12

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Ravindra Balasaheb Patil ,  Rithesh Sreenivasan ,  Krishnamoorthy Palanisamy ,  Nagaraju Bussa

IPC: G06T7/00 ,  A61B1/00 ,  A61B5/055 ,  A61B6/00 ,  A61B6/03 ,  A61B8/08 ,  G06F18/2431 ,  G06N3/08 ,  G16H30/20 ,  G16H30/40 ,  G16H40/20 ,  G16H40/67 ,  G16H50/20

Abstract: A medical imaging system (100, 300, 400, 700) includes a processor and memory with instructions executable by the processor to receive (200) three-dimensional medical image data (122) comprising multiple slices, receive (202) an imaging modality (124) of the three-dimensional medical image data, receive (204) an anatomical view classification (126) of the three-dimensional medical image data, select (206) a chosen abnormality detection module (130) from a set of abnormality detection modules (128) 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 (208) the at least a portion of the multiple slices as normal or abnormal using the abnormality detection module, and choose (210) a set of selected slices (136) from the multiple slices according to a predetermined selection criteria (134) if a predetermined number of the multiple slices are classified as abnormal.

公开(公告)号：US20220375608A1

公开(公告)日：2022-11-24

申请号：US17762755

申请日：2020-10-02

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Ravindra Balasaheb Patil ,  Vidya Ravi ,  Michael Leonardus Helena Boumans ,  Nagaraju Bussa

IPC: G16H50/20 ,  G06N3/08 ,  G06F7/58

Abstract: According to an aspect there is provided a computer-implemented method of monitoring performance of a predictive computer-implemented model, PCIM, that is used to monitor the status of a first system. The PCIM receives as inputs observed values for a plurality of features relating to the first system, and the PCIM determines whether to issue status alerts based on the observed values. The method comprises: obtaining reference information for the PCIM, wherein the reference information for the PCIM comprises a first set of values for the plurality of features relating to the first system in a first time period; determining a set of reference probability distributions from the first set of values, the set of reference probability distributions comprising a respective reference probability distribution for each of the features that is determined from the values of the respective feature in the first set of values; obtaining operational information for the PCIM, wherein the operational information for the PCIM comprises a second set of values for the plurality of features relating to the first system in a second time period that is after the first time period; determining a set of operational probability distributions from the second set of values, the set of operational probability distributions comprising a respective operational probability distribution for each of the features that is determined from the values of the respective feature in the second set of values; determining a drift measure for the PCIM representing a measure of drift in performance of the PCIM between the first time period and the second time period, wherein the drift measure is based on a comparison of the set of reference probability distributions and the set of operational probability distributions; and output the drift measure.

公开(公告)号：US11419559B2

公开(公告)日：2022-08-23

申请号：US16770331

申请日：2018-12-03

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Vikram Basawaraj Patil Okaly ,  Ravindra Balasaheb Patil ,  Rithesh Sreenivasan ,  Krishnamoorthy Palanisamy

IPC: A61B5/00 ,  G16H50/30 ,  A61B5/024 ,  A61B5/11 ,  A61B5/349 ,  G16H40/67 ,  A61B5/0205 ,  A61B5/01 ,  A61B5/08

Abstract: 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.

公开(公告)号：US11823479B2

公开(公告)日：2023-11-21

申请号：US17615299

申请日：2020-06-02

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Sarif Kumar Naik ,  Vidya Ravi ,  Ravindra Balasaheb Patil ,  Meru Adagouda Patil

IPC: G06V30/00 ,  G06V30/422 ,  G06V10/82 ,  G06V30/18 ,  G06V10/426 ,  G06V30/222

CPC classification number: G06V30/422 ,  G06V10/426 ,  G06V10/82 ,  G06V30/18076 ,  G06V30/222

Abstract: A non-transitory computer readable medium (107, 127) stores instructions executable by at least one electronic processor (101, 113) to perform a component co-replacement recommendation method (200). The method includes: identifying components of a medical device by analyzing a technical document (130) related to the medical device; identifying component symbols (132) representing the components in drawings of the technical document; extracting relationships between the components of the medical device based on graphical connections (136) between the component symbols in the drawings of the technical document; generating a component connections graph (124) representing the relationships between the components of the medical device, the graph including nodes (138) corresponding to the components and connections (136) between the components; receiving an identification of a component to be replaced; and determining a co-replacement recommendation (122) for the component to be replaced based on the component connections graph.

公开(公告)号：US11270798B2

公开(公告)日：2022-03-08

申请号：US16316647

申请日：2017-07-12

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Ravindra Balasaheb Patil ,  Krishnamoorthy Palanisamy

IPC: G16H50/20 ,  A61B5/00 ,  G16H50/70 ,  G16H50/50

Abstract: A central signal segregation station (100) employs a signal acquisition controller (103) and a signal segregation controller (104). In operation, the signal acquisition controller (103) receives a plurality of different types of physiological signals from a plurality of unknown physiological sensors (10; 20; 30; 40; 50; 60; 70; 80). For a monitoring of the physiological signals, the signal segregation controller (104) identifies a particular type of each physiological signal based on distinct signal features of each physiological signal corresponding to a different physiological signal model (101) among a plurality of physiological signal models (101) derived from known types of physiological sensors. For analyzing the physiological signals, the station (100) may further employ a signal analyzing controller (105) 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.

公开(公告)号：US10687723B2

公开(公告)日：2020-06-23

申请号：US15744918

申请日：2016-07-12

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Ravindra Balasaheb Patil ,  Rajendra Singh Sisodia ,  Krishnamoorthy Palanisamy ,  Nagaraju Bussa ,  Vikram Basawaraj Patil Okaly ,  Larry Nielsen

IPC: A61B5/0452 ,  A61B5/04 ,  A61B5/00 ,  A61B5/08 ,  A61B5/11 ,  A61B5/0205

Abstract: 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.

公开(公告)号：US11967421B2

公开(公告)日：2024-04-23

申请号：US16981331

申请日：2019-03-06

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Ravindra Balasaheb Patil ,  Meru Adagouda Patil ,  Sarif Kumar Naik ,  Vidya Ravi

IPC: G16H40/40 ,  G06F11/30 ,  G06F40/205 ,  G06F40/211 ,  G06N5/025 ,  G06N5/04 ,  G16H30/00

CPC classification number: G16H40/40 ,  G06F11/30 ,  G06F40/205 ,  G06F40/211 ,  G06N5/025 ,  G06N5/04 ,  G16H30/00

Abstract: In a monitoring method for generating maintenance alerts, component IDs are extracted which identify medical imaging device components in electronic medical imaging device manuals (25, 26, 27, 28). Operating parameters of the medical imaging device components and associated operating parameter ranges are also extracted from the manuals, based on numeric values, parameter terms identifying operating parameters, and linking terms or symbols indicative of equality or inequality that connect the numeric values and parameter terms. The operating parameter ranges are formulated into decision rules (36) which are applied to log data (40) generated by a monitored medical imaging device (2) to detect out-of-range log data generated by the monitored medical imaging device. Maintenance alerts (24) are displayed on a display (18) in response to the detected out-of-range log data. The maintenance alerts are generated from out-of-range log data and are associated with component IDs contained in the out-of-range log data.

公开(公告)号：US11918413B2

公开(公告)日：2024-03-05

申请号：US15772121

申请日：2016-11-02

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Krishnamoorthy Palanisamy ,  Rajendra Singh Sisodia ,  Shriram Sethuraman ,  Ravindra Balasaheb Patil ,  Vikram Basawaraj Patil Okaly

IPC: A61B8/08 ,  A61B8/00 ,  A61B8/06

CPC classification number: A61B8/0891 ,  A61B8/06 ,  A61B8/4411 ,  A61B8/4477 ,  A61B8/4494 ,  A61B8/488

Abstract: 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 (102a) and a second probe (102b) 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.

公开(公告)号：US20190156951A1

公开(公告)日：2019-05-23

申请号：US16316647

申请日：2017-07-12

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Ravindra Balasaheb Patil ,  Krishnamoorthy Palanisamy

IPC: G16H50/20 ,  G16H50/50 ,  A61B5/00

Abstract: A central signal segregation station (100) employs a signal acquisition controller (103) and a signal segregation controller (104). In operation, the signal acquisition controller (103) receives a plurality of different types of physiological signals from a plurality of unknown physiological sensors (10; 20; 30; 40; 50; 60; 70; 80). For a monitoring of the physiological signals, the signal segregation controller (104) identifies a particular type of each physiological signal based on distinct signal features of each physiological signal corresponding to a different physiological signal model (101) among a plurality of physiological signal models (101) derived from known types of physiological sensors. For analyzing the physiological signals, the station (100) may further employ a signal analyzing controller (105) 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.