Scholarlink

Artificial Intelligence (AI) has found wide use among medical imaging modalities including magnetic resonance imaging (MRI). While many methods developed are applied post-acquisition for image reconstruction and enhancement, AI can also be applied pre-acquisition by optimizing acquisition protocols and scanner operation. With AI developments in this field, a future revolutionized by techniques in this field could lead to the implementation of autonomous, self-driven MRI scanners with optimized pulse sequences curated for an individual patient. This chapter delves into these developments, exploring their current and future impact on the domain of MRI.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Impact of Artificial Intelligence (AI) on Pulse Sequence Design and Its Translation to Clinic

  • 章节

  • 发表日期：

    2025年

查看全文
  • James H. Wang,
  • Alan B. McMillan

摘要

Artificial Intelligence (AI) has found wide use among medical imaging modalities including magnetic resonance imaging (MRI). While many methods developed are applied post-acquisition for image reconstruction and enhancement, AI can also be applied pre-acquisition by optimizing acquisition protocols and scanner operation. With AI developments in this field, a future revolutionized by techniques in this field could lead to the implementation of autonomous, self-driven MRI scanners with optimized pulse sequences curated for an individual patient. This chapter delves into these developments, exploring their current and future impact on the domain of MRI.