Integrating artificial intelligence in medical imaging for precision therapy: The role of ai in segmentation, laser-guided procedures, and protective shielding
The rapid integration of artificial intelligence (AI) in medical imaging has transformed the healthcare landscape, enabling precision therapy for a range of diseases. This article explores the key roles of AI in medical imaging, particularly focusing on three vital areas: segmentation, laser-guided procedures, and protective shielding. AI-driven segmentation tools offer unprecedented accuracy in identifying pathological regions, improving diagnostic efficiency, and aiding in personalized treatment plans. Laser-guided procedures, powered by AI algorithms, provide enhanced precision in targeting affected tissues, minimizing damage to healthy tissues, and promoting faster recovery times. Additionally, AI has made significant strides in optimizing protective shielding techniques, ensuring patient safety while minimizing radiation exposure during imaging and therapy. The article discusses the technological advances, clinical applications, challenges, and future directions of AI in these domains. Through this synthesis, the potential of AI to revolutionize medical imaging and contribute to more effective, safer, and personalized therapies becomes evident.
Institutions
- University of Arkansas at Little Rock (US)
- New York Medical College (US)
- Babcock University (NG)
- South Jordan Health Center (US)
- Indiana University – Purdue University Indianapolis (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-09-30
- DOI
- https://doi.org/10.5281/zenodo.14942537
- Primary Topic
- Advanced Radiotherapy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00