DEEP LEARNING-BASED REAL-TIME EYE-GAZE TRACKING FOR PORTABLE ULTRASOUND METHOD AND APPARATUS

    公开(公告)号:US20240164757A1

    公开(公告)日:2024-05-23

    申请号:US18282342

    申请日:2022-03-16

    CPC classification number: A61B8/469 A61B8/4427 A61B8/463 A61B8/54 G06F3/013

    Abstract: An ultrasound portable system (10) and method comprise acquiring ultrasound images, via a smart device (14) and ultrasound probe (20), over a portion of an ultrasound scan protocol and/or ultrasound exam and presenting at least one acquired ultrasound image in an image space portion (24) of a display (16). Digital images are acquired, via a camera (18), of at least a device operator's head pose, and left and right eyes within respective digital images. Eye-gaze focus point locations on the smart device are determined within a combination of image space and control space (26) portions of the display via an image processing framework (36) configured to track the device operator's gaze and eye movement determined from the acquired digital images. The method further comprises performing a control function, selection of a control function, and/or a function to aid in a selection of a diagnostic measurement based on at least one determined eye-gaze focus point location of the determined eye-gaze focus point locations.

    Camera and image calibration for subject identification

    公开(公告)号:US11232287B2

    公开(公告)日:2022-01-25

    申请号:US16647196

    申请日:2018-09-11

    Abstract: In various embodiments, a first plurality of digital images captured by a first camera (256, 456, 1156) of a first area may be categorized (1202-1210) into multiple predetermined categories based on visual attribute(s) of the first plurality of digital images. A second plurality of digital images captured by a second camera (276, 376, 476, 1176) of a second area may be categorized (1302-1310) into the same predetermined categories based on visual attribute(s) of the second plurality of digital images. After the second camera acquires (1402) a subsequent digital image depicting an unknown subject in the second area, the subsequent digital image may be categorized (1404-1406) into a given one of the predetermined categories based on its visual attribute(s), and then adjusted (1408) based on a relationship between the first plurality of digital images categorized into the given category and the second plurality of digital images categorized into the given category.

    Subject identification systems and methods

    公开(公告)号:US10832035B2

    公开(公告)日:2020-11-10

    申请号:US16014046

    申请日:2018-06-21

    Abstract: Disclosed techniques relate to identifying subjects in digital images. In various embodiments, digital image(s) that depict a subject in an area may be acquired. Portion(s) of the digital image(s) that depict a face of the subject may be detected as detected face image(s). Features of each of the detected face image(s) may be compared with features of each of a set of subject reference templates associated with a given subject in a subject reference database. Based on the comparing, a subject reference template may be selected from the set of subject reference templates associated with the given subject. Similarity measure(s) may then be determined between a given detected face image of the detected face image(s) and the selected subject reference template. An identity of the subject may be determined based on the similarity measure(s).

    Patient identification systems and methods

    公开(公告)号:US10997397B2

    公开(公告)日:2021-05-04

    申请号:US16463484

    申请日:2017-11-22

    Abstract: Disclosed techniques relate to identifying subjects in digital images. In some embodiments, intake digital images (404) are acquired (1002) that capture a first subject. A subset of the intake digital images is selected (1004) that depict multiple different views of the first subject's face. Based on the selected subset of intake digital images, first subject reference templates are generated and stored in a subject database (412). Later, a second subject is selected (1008) for identification within an area. Associated second subject reference templates are retrieved (1010) from the subject reference database. Digital image(s) (420) that depict the area are acquired (1012). Portion(s) of the digital image(s) that depict faces of subject(s) in the area are detected (1014) as detected face image(s). A given detected face image is compared (1016) to the second subject reference templates to identify the second subject (1018) in the digital image(s) that capture the area.

    SUBJECT IDENTIFICATION SYSTEMS AND METHODS
    9.
    发明申请

    公开(公告)号:US20180373925A1

    公开(公告)日:2018-12-27

    申请号:US16014046

    申请日:2018-06-21

    Abstract: Disclosed techniques relate to identifying subjects in digital images. In various embodiments, digital image(s) that depict a subject in an area may be acquired. Portion(s) of the digital image(s) that depict a face of the subject may be detected as detected face image(s). Features of each of the detected face image(s) may be compared with features of each of a set of subject reference templates associated with a given subject in a subject reference database. Based on the comparing, a subject reference template may be selected from the set of subject reference templates associated with the given subject. Similarity measure(s) may then be determined between a given detected face image of the detected face image(s) and the selected subject reference template. An identity of the subject may be determined based on the similarity measure(s).

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