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- Challenges Related to Artificial Intelligence Research in . . .
However, important roadblocks currently limit the expansion of this field in medical imaging This article reviews some of the challenges and potential solutions to advance the field forward, with focus on the experience gained by hosting image-based competitions
- The Good, the Bad, and the Ugly of AI in Medical Imaging
While the potential benefits of AI in medical imaging are immense, it is also crucial to acknowledge the potential risks and limitations of its use within the medical field 1 AI algorithms can analyse medical images with remarkable accuracy and speed, often surpassing human capabilities
- The Future of Sonography: Understanding the Limitations of AI . . .
Although AI technology has the potential to reshape the field of ultrasound, the unique challenges and operator dependency of ultrasound exams present barriers to full automation Current applications focus on operator guidance to standardize image acquisition, often with real-time feedback on image quality
- Computational biomedical imaging: AI innovations and pitfalls
Despite these successes, medical image analysis faces a major limitation: the scarcity of large-scale datasets compared to fields like general computer vision or natural language processing
- The Challenges and Solutions in Modern Medical Imaging
Every imaging modality has its limitations For instance, CT scans do not have the sensitivity level for early disease detection, and MRIs are highly time-consuming and expensive The quality of the equipment, the operator's skill, and the patient's condition determine the image's quality
- Future Perspectives in Radiology: Artificial Intelligence for . . .
However, the overuse and misuse of imaging is still a major ongoing problem, generating unnecessary costs, radiation exposure to patients, and delays in diagnosis To address these challenges, we propose AI for responsible imaging (AIRI), a multimodal AI system to aid clinicians in making informed imaging decisions
- Grand Challenges in Radiology - PMC
We will address specific challenges associated the six sub-fields of radiology, namely, neuroradiology, diagnostic radiology, interventional radiology, emergency radiology, cardiothoracic imaging, and AI in radiology
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