Leveraging Vertex AI for Automated Ultrasound Image Analysis: A Comprehensive Review

Abstract: The integration of artificial intelligence (AI) into clinical ultrasound imaging presents profound opportunities for advancing diagnostic accuracy, streamlining workflow efficiency, and ultimately improving patient outcomes. This comprehensive review synthesizes contemporary literature and industry frameworks to evaluate current advances, practical use cases, observed performance, and inherent limitations of Google Cloud's Vertex AI when applied to clinical ultrasound imaging studies.¹ The platform's capabilities are not merely incremental; they represent a potential paradigm shift in how clinical ultrasound diagnostics are approached and executed. This fundamental change can lead to reduced human variability in interpretation, optimized resource allocation within healthcare systems, and faster patient diagnoses, though it also implicitly raises questions about associated regulatory, ethical, and integration challenges that warrant careful consideration.

Artificial intelligence (AI), Clinical ultrasound imaging, Vertex AI, Google Cloud, Machine learning in healthcare, Medical imaging automation

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