# US 12,183,008 B2 · Device agnostic systems and methods for acquiring and analyzing images from an ultrasound probe > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,183,008 B2 - Document ID: US12183008B2 - Status: Granted - Kind: B2 - Application number: 18/168,402 - Filed: 2023-02-13 - Published: 2024-08-15 - Granted: 2024-12-31 - Earliest claimed: 2023-02-13 - Assignees: Exo Imaging, Inc. - Applicants: Exo Imaging, Inc. - Inventors: Roberto Ivan Vega Romero; Seyed Ehsan Seyed Bolouri; Amirhosein Forouzandehmoghadam; Amir Safarpoor Kordbacheh; Mahdiar Nekoui; Masood Dehghan; Dornoosh Zonoobi - Web page: https://patentgrep.com/patent/US12183008B2 ## CPC - G06T 7/0016: {involving temporal comparison} - A61B 8/085: {for locating body or organic structures, e.g. tumours, calculi, blood vessels, nodules} - A61B 8/4245: {involving determining the position of the probe, e.g. with respect to an external reference frame or to the patient} - A61B 8/4477: {using several separate ultrasound transducers or probes} - A61B 8/461: {Displaying means of special interest} - A61B 8/469: {for selection of a region of interest} - A61B 8/5207: {involving processing of raw data to produce diagnostic data, e.g. for generating an image} - A61B 8/5246: {combining images from the same or different imaging techniques, e.g. color Doppler and B-mode} - A61B 8/5269: {involving detection or reduction of artifacts} - A61B 8/5292: {using additional data, e.g. patient information, image labeling, acquisition parameters} - A61B 8/54: {Control of the diagnostic device} - G06T 3/4046: using neural networks - G06T 7/0014: {using an image reference approach} - G06T 7/11: Region-based segmentation - G06T 7/174: involving the use of two or more images - G06T 2200/24: involving graphical user interfaces [GUIs] - G06T 2207/10132: Ultrasound image - G06T 2207/20081: Training; Learning - G06T 2207/20084: Artificial neural networks [ANN] - G06T 2207/20224: Image subtraction - G06T 2207/30004: Biomedical image processing - G06T 2207/30168: Image quality inspection - G06T 2207/30204: Marker - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) ## Abstract A method includes obtaining a first frame of a probed region acquired using a first probe device at a first time, and a first set of control parameters used to acquire the first frame. Processing the first frame includes segmenting features from the first frame after first probe-specific effects are reduced in the first frame based on the first set of control parameters. The method includes, when the first frame contains a respective attribute present in a second frame acquired at a time earlier than the first time using a second set of control parameters, displaying information related to differences in the respective attribute in the first frame and the second frame. The second frame is obtained by processing the one or more features segmented from the second frame after one or more second probe-specific effects are reduced in the second frame. ## Claims ### Claim 1 A method, comprising: at a computer system that includes one or more processors and memory: obtaining a first frame of a probed region acquired using a first probe device at a first time, and a first set of control parameters used to acquire the first frame; processing the first frame to obtain a first set of attributes of the first frame, wherein processing the first frame includes segmenting one or more features from the first frame after one or more first probe-specific effects are reduced in the first frame based at least in part on the first set of control parameters; in accordance with a determination that the first frame contains a respective attribute present in a second frame acquired at a time earlier than the first time using a second set of control parameters: displaying, on a user interface, information related to differences in the respective attribute based on the first frame and the second frame, wherein the second frame is obtained by processing the one or more features segmented from the second frame after one or more second probe-specific effects are reduced in the second frame. ### Claim 2 (depends on 1) The method of claim 1, wherein reducing the one or more first probe-specific effects in the first frame comprises one or more elements selected from the group consisting of: preprocessing the first frame to account for the first set of control parameters and the second set of control parameters, and removing noise from the first frame. ### Claim 3 (depends on 2) The method of claim 2, wherein preprocessing the first frame to account for the first set of control parameters comprises resizing pixels in the first frame, and removing noise from the first frame comprises subtracting noise from the first frame using a noise profile specific to the first probe device, and rescaling a magnitude of values associated with respective pixels in the first frame. ### Claim 4 (depends on 3) The method of claim 3, wherein rescaling the magnitude of the values associated with the respective pixels to a rescaled range comprises using machine learning to dynamically determine the rescaled range. ### Claim 5 (depends on 1) The method of claim 1, wherein segmenting the one or more features from the first frame comprises segmenting the one or more features from the first frame using one or more spatial locations derived from the second frame. ### Claim 6 (depends on 5) The method of claim 5, wherein segmenting the first frame into the one or more features based on the spatial locations derived from the second frame includes obtaining the spatial locations from a template, and the method further includes performing a local search in a window centered at coordinates corresponding to the spatial locations. ### Claim 7 (depends on 1) The method of claim 1, wherein displaying the information related to differences in the respective attribute includes displaying information about changes to the one or more segmented features that are clinically relevant. ### Claim 8 (depends on 1) The method of claim 1, wherein processing the one or more features segmented from the second frame comprises mapping the one or more features onto a template. ### Claim 9 (depends on 8) The method of claim 8, wherein the template includes one or more markers that identify locations of one or more anatomical regions of interest, the one or more anatomical regions of interest include a first anatomical region of interest in which the respective attribute is located. ### Claim 10 (depends on 1) The method of claim 1, wherein the second frame is acquired using a second probe device different from the first probe device. ### Claim 11 (depends on 1) The method of claim 1, further comprising: in accordance with a determination that the first frame fails to meet a first criteria related to an anatomical region of interest: providing guidance for positioning the first probe device at a different location from a location where the first frame was acquired to obtain a third frame of a structure within the anatomical region of interest, the third frame having a higher image quality metric compared to the first frame. ### Claim 12 (depends on 11) The method of claim 11, further comprising: generating a statistical model based on the one or more features to determine a presence of an anatomical region of interest in the first frame. ### Claim 13 (depends on 11) The method of claim 11, further comprising: in accordance with a determination that the first criteria related to the anatomical region of interest have been met, computing a metric of interest associated with the structure. ### Claim 14 (depends on 11) The method of claim 11, further comprising: processing the third frame by segmenting one or more features from the third frame after one or more probe-specific effects are reduced in the third frame, and displaying, on the user interface, information related to differences in the structure based on the third frame and the second frame. ### Claim 15 (depends on 14) The method of claim 14, wherein the third frame is obtained from approximately a same plane and/or in a comparable field of view as the second frame. ### Claim 16 (depends on 1) The method of claim 1, wherein the one or more features segmented from the first frame comprise features that are invariant to the first probe device. ### Claim 17 (depends on 1) The method of claim 1, wherein the first frame is obtained by selecting a frame from a plurality of frames acquired in a sweep. ### Claim 18 (depends on 1) The method of claim 1, further comprising: obtaining the second frame of the probed region acquired using a second probe device, and the second set of control parameters used to acquire the second frame; and processing the second frame to obtain a second set of attributes of the second frame, wherein processing the second frame includes segmenting one or more features from the second frame after one or more second probe-specific effects are reduced in the second frame based at least in part on the second set of control parameters. ### Claim 19 A non-transitory computer-readable storage medium having stored thereon program code instructions that, when executed by a processor, cause the processor to perform operations comprising: obtaining a first frame of a probed region acquired using a first probe device at a first time, and a first set of control parameters used to acquire the first frame; processing the first frame to obtain a first set of attributes of the first frame, wherein processing the first frame includes segmenting one or more features from the first frame after one or more first probe-specific effects are reduced in the first frame based at least in part on the first set of control parameters; in accordance with a determination that the first frame contains a respective attribute present in a second frame acquired at a time earlier than the first time using a second set of control parameters: displaying, on a user interface, information related to differences in the respective attribute based on the first frame and the second frame, wherein the second frame is obtained by processing the one or more features segmented from the second frame after one or more second probe-specific effects are reduced in the second frame. ### Claim 20 A computer system, comprising: one or more processors; and memory storing one or more programs, the one or more programs comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: obtaining a first frame of a probed region acquired using a first probe device at a first time, and a first set of control parameters used to acquire the first frame; processing the first frame to obtain a first set of attributes of the first frame, wherein processing the first frame includes segmenting one or more features from the first frame after one or more first probe-specific effects are reduced in the first frame based at least in part on the first set of control parameters; in accordance with a determination that the first frame contains a respective attribute present in a second frame acquired at a time earlier than the first time using a second set of control parameters: displaying, on a user interface, information related to differences in the respective attribute based on the first frame and the second frame, wherein the second frame is obtained by processing the one or more features segmented from the second frame after one or more second probe-specific effects are reduced in the second frame.