The iSeg AI platform matches or outperforms physicians in segmenting lung tumors on CT scans, aiding radiation therapy planning.
Key Details
- 1iSeg was developed by Northwestern Medicine researchers for lung tumor segmentation.
- 2Tested on CT scans, iSeg matched or exceeded physician performance in outlining tumor margins.
- 3In some cases, the AI identified tumor regions missed by doctors.
- 4iSeg was trained and validated on a multi-institutional dataset from nine centers, featuring hundreds of CT scans plus manual segmentations.
- 5Experts believe this tool could enhance precision in radiation therapy.
Why It Matters
Accurate tumor segmentation is critical for effective radiation therapy planning. AI solutions like iSeg may improve treatment precision, reduce physician workload, and uncover areas potentially overlooked by human experts.
Source
Health Imaging
Related News
•Radiology Business
Framework Assesses Real-World Financial Impact of Radiology AI Adoption
A new analysis presents a financial calculator for objectively assessing the return on investment (ROI) of implementing radiology AI solutions.
•Radiology Business
AI Technique Unveils Previously Hidden MS Gray Matter Lesions on MRI
Researchers developed an AI-enhanced method to detect previously invisible gray matter lesions in multiple sclerosis using MRI.
•Radiology Business
Majority of Patients Want Disclosure When AI Used in Imaging
A new survey finds that nearly all patients want to be informed when AI is utilized in medical imaging interpretation.