Dataset Information

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 in the past 5 years. The date range was from 1 January 2018 to 1 June 2023. A total of 78 English articles were reviewed.

Key content and findings

We introduce public datasets, evaluation methods, and multi-modal data processing. We also summarize common DL network structures, techniques, and multi-modal image fusion methods used in different tumor segmentation tasks. Finally, we conclude this study by presenting perspectives for future research.

Conclusions

In multi-modal tumor segmentation tasks, DL technique is a powerful method. With the fusion methods of different modal data, the DL framework can effectively use the characteristics of different modal data to improve the accuracy of tumor segmentation.

SUBMITTER: Xue H

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

REPOSITORIES: biostudies-literature

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Publications

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

Xue Hengzhi H Yao Yudong Y Teng Yueyang Y

Quantitative imaging in medicine and surgery 20240102 1

<h4>Background and objective</h4>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 signif ...[more]

PMID: 38223046

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Dataset Information

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

Background and objective

Methods

Key content and findings

Conclusions

Publications

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

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