A deep learning-based diagnostic pattern for ultrasound breast imaging: can it reduce unnecessary biopsy?

ABSTRACT:

Background

Early studies have demonstrated the potential of deep learning in bringing revolutionary changes in medical analysis. However, it is unknown which deep learning based diagnostic pattern is more effective for differentiating malignant and benign breast lesions (BLs) and can assist radiologists to reduce unnecessary biopsies.

Methods

A total of 506 malignant BLs and 557 benign BLs were enrolled in this study after excluding incomplete ultrasound images. 396 malignant BLs and 447 benign BLs were included in the training cohort while 110 malignant and 110 benign BLs were included in the validation cohort. All BLs in the training and validation cohort were biopsy-proven. The most common convolutional neural networks (VGG-16 and VGG-19) were applied to identify malig

SUBMITTER: Zhu Y 

PROVIDER: S-EPMC9547710 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature