Abstract
Artificial intelligence (AI) in radiology is transforming medical image analysis. While applications in triaging for priority reporting and radiomic feature analysis have been widely reported, perhaps the most important applications lie in noise reduction, image optimization following dose reduction strategies, image reconstruction direct from projection data and generation of pseudo-CT for attenuation correction. There are common beneficial applications, and potential risks, between human radiology and veterinary radiology. Artificial intelligence may see recrafting of some responsibilities but offers AI augmentation of human driven systems. The redundancy afforded by human augmentation of AI and AI autonomy are not on the horizon, but rather are already here.
Original language | English (US) |
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Pages (from-to) | 880-888 |
Number of pages | 9 |
Journal | Veterinary Radiology and Ultrasound |
Volume | 63 Suppl 1 |
Issue number | S1 |
DOIs |
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State | Published - Dec 2022 |
Keywords
- artificial intelligence
- artificial neural network
- convolutional neural network
- deep learning
- medical imaging
- radiology
- Humans
- Artificial Intelligence
- Machine Learning
- Deep Learning
- Animals
- Image Processing, Computer-Assisted
- Radiology
ASJC Scopus subject areas
- veterinary(all)