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公开(公告)号：US20180197288A1
公开(公告)日：2018-07-12
申请号：US15401884
申请日：2017-01-09
Applicant: General Electric Company
Inventor： Camila Patricia Bazilio Nunes , Marina Lundgren de Almeida Magalhaes , Marcelo Blois Ribeiro , Dario Augusto Borges Oliveira , Eudemberg Fonseca Silva , Felipe Santos De Andrade , Marco Blumenthal , Giovanni John Jacques Palma , Serge Louis Wilfrid Mueller
CPC classification number: G06T7/0012 , A61B6/4405 , A61B6/502 , A61B6/5258 , A61B6/563 , A61B6/586 , G01T7/00 , G06F19/321 , G06T2207/10116 , G06T2207/30068
Abstract: The present approach relates to providing image quality feedback to personnel (e.g., a technician) acquiring non-invasive images in real-time or near real-time. By way of example, the proposed approach may automatically assess the quality of images in real-time by evaluating the images for the presence or absence of non-conformities using processor-implemented, rule-based algorithms running partly or completely in parallel to one another. The proposed approach improves the image analysis pipeline by efficiently providing notification of and/or discarding low-quality or unsuitable images or exams after they are taken, such as in within seconds or minutes.
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公开(公告)号：US10282838B2
公开(公告)日：2019-05-07
申请号：US15401884
申请日：2017-01-09
Applicant: General Electric Company
Inventor： Camila Patricia Bazilio Nunes , Marina Lundgren de Almeida Magalhaes , Marcelo Blois Ribeiro , Dario Augusto Borges Oliveira , Eudemberg Fonseca Silva , Felipe Santos De Andrade , Marco Blumenthal , Giovanni John Jacques Palma , Serge Louis Wilfrid Mueller
Abstract: The present approach relates to providing image quality feedback to personnel (e.g., a technician) acquiring non-invasive images in real-time or near real-time. By way of example, the proposed approach may automatically assess the quality of images in real-time by evaluating the images for the presence or absence of non-conformities using processor-implemented, rule-based algorithms running partly or completely in parallel to one another. The proposed approach improves the image analysis pipeline by efficiently providing notification of and/or discarding low-quality or unsuitable images or exams after they are taken, such as in within seconds or minutes.
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