| CPC A61B 34/20 (2016.02) [A61B 5/062 (2013.01); A61B 5/318 (2021.01); A61B 8/0841 (2013.01); A61B 8/0891 (2013.01); G06N 20/10 (2019.01); G16H 30/20 (2018.01); A61B 2034/2063 (2016.02)] | 17 Claims |
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1. A target recognition and needle guidance system, comprising:
a console including a processor and non-transitory, computer-readable medium having stored thereon logic that, when executed by the processor, is configured to initiate:
a target recognition process configured to (1) receive user input indicating a desired target, and (ii) identify a blood vessel of a patient corresponding to the desired target by applying a machine learning model to features of candidate targets in ultrasound-imaging data, wherein the blood vessel identified as the desired target is associated with a highest confidence score determined by the machine learning model, and
a needle guidance process for guiding insertion of a needle into the blood vessel identified as the desired target by the machine learning model, wherein the machine learning model determines a proximity of a trajectory of the needle to the blood vessel identified as the desired target based on magnetic information about the needle, and wherein a catheter is implanted into the blood vessel identified as the desired target following the insertion of the needle; and
an ultrasound probe configured to provide to the console electrical signals corresponding to the ultrasound-imaging data, the ultrasound probe including:
an array of transducers configured to convert reflected ultrasound signals from the patient into an ultrasound-imaging portion of the electrical signals, and a magnetic sensor configured to provide to the console second electrical signals corresponding to the magnetic information about the needle.
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