Application of Artificial Intelligence in Medical Imaging: Current Status and Future Directions
ABSTRACT A revolution in medical diagnosis and treatment is being driven by the use of artificial intelligence (AI) in medical imaging. The diagnostic efficacy and accuracy of medical imaging are greatly enhanced by AI technologies, especially deep learning, that performs image recognition, feature...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-04-01
|
| Series: | iRADIOLOGY |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ird3.70008 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849715475990183936 |
|---|---|
| author | Yixin Yang Lan Ye Zhanhui Feng |
| author_facet | Yixin Yang Lan Ye Zhanhui Feng |
| author_sort | Yixin Yang |
| collection | DOAJ |
| description | ABSTRACT A revolution in medical diagnosis and treatment is being driven by the use of artificial intelligence (AI) in medical imaging. The diagnostic efficacy and accuracy of medical imaging are greatly enhanced by AI technologies, especially deep learning, that performs image recognition, feature extraction, and pattern analysis. Furthermore, AI has demonstrated significant promise in assessing the effects of treatments and forecasting the course of diseases. It also provides doctors with more advanced tools for managing the conditions of their patients. AI is poised to play a more significant role in medical imaging, especially in real‐time image processing and multimodal fusion. By integrating multiple forms of image data, multimodal fusion technology provides more comprehensive disease information, whereas real‐time image analysis can assist surgeons in making more precise decisions. By tailoring treatment regimens to each patient's unique needs, AI enhances both the effectiveness of treatment and the patient experience. Overall, AI in medical imaging promises a bright future, significantly enhancing diagnostic precision and therapeutic efficacy, and ultimately delivering higher‐quality medical care to patients. |
| format | Article |
| id | doaj-art-119f356ad39b4f27a32d4ca0c8ee4cb7 |
| institution | DOAJ |
| issn | 2834-2860 2834-2879 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | iRADIOLOGY |
| spelling | doaj-art-119f356ad39b4f27a32d4ca0c8ee4cb72025-08-20T03:13:22ZengWileyiRADIOLOGY2834-28602834-28792025-04-013214415110.1002/ird3.70008Application of Artificial Intelligence in Medical Imaging: Current Status and Future DirectionsYixin Yang0Lan Ye1Zhanhui Feng2School of Health Science and Engineering University of Shanghai for Science and Technology Shanghai ChinaSchool of Basic Medicine Guizhou Medical University Guiyang ChinaDepartment of Neurology Guizhou Provincial People's Hospital Guiyang ChinaABSTRACT A revolution in medical diagnosis and treatment is being driven by the use of artificial intelligence (AI) in medical imaging. The diagnostic efficacy and accuracy of medical imaging are greatly enhanced by AI technologies, especially deep learning, that performs image recognition, feature extraction, and pattern analysis. Furthermore, AI has demonstrated significant promise in assessing the effects of treatments and forecasting the course of diseases. It also provides doctors with more advanced tools for managing the conditions of their patients. AI is poised to play a more significant role in medical imaging, especially in real‐time image processing and multimodal fusion. By integrating multiple forms of image data, multimodal fusion technology provides more comprehensive disease information, whereas real‐time image analysis can assist surgeons in making more precise decisions. By tailoring treatment regimens to each patient's unique needs, AI enhances both the effectiveness of treatment and the patient experience. Overall, AI in medical imaging promises a bright future, significantly enhancing diagnostic precision and therapeutic efficacy, and ultimately delivering higher‐quality medical care to patients.https://doi.org/10.1002/ird3.70008artificial intelligenceautomationcomputer visiondeep learningmedical imagingmulti‐modal image data |
| spellingShingle | Yixin Yang Lan Ye Zhanhui Feng Application of Artificial Intelligence in Medical Imaging: Current Status and Future Directions iRADIOLOGY artificial intelligence automation computer vision deep learning medical imaging multi‐modal image data |
| title | Application of Artificial Intelligence in Medical Imaging: Current Status and Future Directions |
| title_full | Application of Artificial Intelligence in Medical Imaging: Current Status and Future Directions |
| title_fullStr | Application of Artificial Intelligence in Medical Imaging: Current Status and Future Directions |
| title_full_unstemmed | Application of Artificial Intelligence in Medical Imaging: Current Status and Future Directions |
| title_short | Application of Artificial Intelligence in Medical Imaging: Current Status and Future Directions |
| title_sort | application of artificial intelligence in medical imaging current status and future directions |
| topic | artificial intelligence automation computer vision deep learning medical imaging multi‐modal image data |
| url | https://doi.org/10.1002/ird3.70008 |
| work_keys_str_mv | AT yixinyang applicationofartificialintelligenceinmedicalimagingcurrentstatusandfuturedirections AT lanye applicationofartificialintelligenceinmedicalimagingcurrentstatusandfuturedirections AT zhanhuifeng applicationofartificialintelligenceinmedicalimagingcurrentstatusandfuturedirections |