Automated Placement of Scan and Pre-Scan Volumes for Breast MRI Using a Convolutional Neural Network.

ABSTRACT: Graphically prescribed patient-specific imaging volumes and local pre-scan volumes are routinely placed by MRI technologists to optimize image quality. However, manual placement of these volumes by MR technologists is time-consuming, tedious, and subject to intra- and inter-operator variability. Resolving these bottlenecks is critical with the rise in abbreviated breast MRI exams for screening purposes. This work proposes an automated approach for the placement of scan and pre-scan volumes for breast MRI. Anatomic 3-plane scout image series and associated scan volumes were retrospectively collected from 333 clinical breast exams acquired on 10 individual MRI scanners. Bilateral pre-scan volumes were also generated and reviewed in consensus by three MR physicists. A deep convolutional neura

SUBMITTER: Allen TJ 

PROVIDER: S-EPMC10204486 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature