Multi-modal tumor segmentation methods based on deep learning: a narrative review.

ABSTRACT:

Background and objective

Automatic tumor segmentation is a critical component in clinical diagnosis and treatment. Although single-modal imaging provides useful information, multi-modal imaging provides a more comprehensive understanding of the tumor. Multi-modal tumor segmentation has been an essential topic in medical image processing. With the remarkable performance of deep learning (DL) methods in medical image analysis, multi-modal tumor segmentation based on DL has attracted significant attention. This study aimed to provide an overview of recent DL-based multi-modal tumor segmentation methods.

Methods

In in the PubMed and Google Scholar databases, the keywords "multi-modal", "deep learning", and "tumor segmentation" were used to systematically search English articles

SUBMITTER: Xue H 

PROVIDER: S-EPMC10784092 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature