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
•AuntMinnie
Machine Learning Model Enhances Risk Stratification for Prostate MRI
Researchers developed machine learning models that outperform PSA testing in predicting abnormal prostate MRI findings for suspected prostate cancer.
•AuntMinnie
AI's Evolving Role in Tackling Radiology Workforce Shortages
AI technologies are emerging as key tools to alleviate radiology workforce shortages by improving efficiency and supporting clinical workflows.
•Radiology Business
Multimodal LLMs Struggle with Radiology Board Image Questions
Latest multimodal large language models show limitations on image-based radiology exam questions.