Modality preserving U-Net for segmentation of multimodal medical images.

ABSTRACT:

Background

Recent advances in artificial intelligence and digital image processing have inspired the use of deep neural networks for segmentation tasks in multimodal medical imaging. Unlike natural images, multimodal medical images contain much richer information regarding different modal properties and therefore present more challenges for semantic segmentation. However, there is no report on systematic research that integrates multi-scaled and structured analysis of single-modal and multimodal medical images.

Methods

We propose a deep neural network, named as Modality Preserving U-Net (MPU-Net), for modality-preserving analysis and segmentation of medical targets from multimodal medical images. The proposed MPU-Net consists of a modality preservation encoder (MPE) module t

SUBMITTER: Wu B 

PROVIDER: S-EPMC10423364 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature