A survey on automatic generation of medical imaging reports based on deep learning
Abstract Recent advances in deep learning have shown great potential for the automatic generation of medical imaging reports. Deep learning techniques, inspired by image captioning, have made significant progress in the field of diagnostic report generation. This paper provides a comprehensive overv...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-05-01
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| Series: | BioMedical Engineering OnLine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12938-023-01113-y |
| _version_ | 1797822730101325824 |
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| author | Ting Pang Peigao Li Lijie Zhao |
| author_facet | Ting Pang Peigao Li Lijie Zhao |
| author_sort | Ting Pang |
| collection | DOAJ |
| description | Abstract Recent advances in deep learning have shown great potential for the automatic generation of medical imaging reports. Deep learning techniques, inspired by image captioning, have made significant progress in the field of diagnostic report generation. This paper provides a comprehensive overview of recent research efforts in deep learning-based medical imaging report generation and proposes future directions in this field. First, we summarize and analyze the data set, architecture, application, and evaluation of deep learning-based medical imaging report generation. Specially, we survey the deep learning architectures used in diagnostic report generation, including hierarchical RNN-based frameworks, attention-based frameworks, and reinforcement learning-based frameworks. In addition, we identify potential challenges and suggest future research directions to support clinical applications and decision-making using medical imaging report generation systems. |
| first_indexed | 2024-03-13T10:13:28Z |
| format | Article |
| id | doaj.art-4bd079307aa04497bcc291ab350ae1d8 |
| institution | Directory Open Access Journal |
| issn | 1475-925X |
| language | English |
| last_indexed | 2024-03-13T10:13:28Z |
| publishDate | 2023-05-01 |
| publisher | BMC |
| record_format | Article |
| series | BioMedical Engineering OnLine |
| spelling | doaj.art-4bd079307aa04497bcc291ab350ae1d82023-05-21T11:22:00ZengBMCBioMedical Engineering OnLine1475-925X2023-05-0122111610.1186/s12938-023-01113-yA survey on automatic generation of medical imaging reports based on deep learningTing Pang0Peigao Li1Lijie Zhao2Center of Network and Information, Xinxiang Medical UniversityCenter of Network and Information, Xinxiang Medical UniversityCenter of Network and Information, Xinxiang Medical UniversityAbstract Recent advances in deep learning have shown great potential for the automatic generation of medical imaging reports. Deep learning techniques, inspired by image captioning, have made significant progress in the field of diagnostic report generation. This paper provides a comprehensive overview of recent research efforts in deep learning-based medical imaging report generation and proposes future directions in this field. First, we summarize and analyze the data set, architecture, application, and evaluation of deep learning-based medical imaging report generation. Specially, we survey the deep learning architectures used in diagnostic report generation, including hierarchical RNN-based frameworks, attention-based frameworks, and reinforcement learning-based frameworks. In addition, we identify potential challenges and suggest future research directions to support clinical applications and decision-making using medical imaging report generation systems.https://doi.org/10.1186/s12938-023-01113-yMedical imaging reportsAutomatic generationImage captioningDeep learning |
| spellingShingle | Ting Pang Peigao Li Lijie Zhao A survey on automatic generation of medical imaging reports based on deep learning BioMedical Engineering OnLine Medical imaging reports Automatic generation Image captioning Deep learning |
| title | A survey on automatic generation of medical imaging reports based on deep learning |
| title_full | A survey on automatic generation of medical imaging reports based on deep learning |
| title_fullStr | A survey on automatic generation of medical imaging reports based on deep learning |
| title_full_unstemmed | A survey on automatic generation of medical imaging reports based on deep learning |
| title_short | A survey on automatic generation of medical imaging reports based on deep learning |
| title_sort | survey on automatic generation of medical imaging reports based on deep learning |
| topic | Medical imaging reports Automatic generation Image captioning Deep learning |
| url | https://doi.org/10.1186/s12938-023-01113-y |
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