Synthetic tumor data enhances training for cancer detection AI

A Johns Hopkins University-led team of researchers has created a method to generate large datasets of synthetic liver tumor computed tomography (CT) scans, which could aid in the training of cancer detection algorithms.

The generation of artificial, automatically annotated tumor images could help address an ongoing scarcity of high-quality data used to train AI to identify early-stage cancer. Flagging tumors on medical scans is a time-consuming process that often requires interpreting pathology reports and waiting for biopsy confirmations, making large-scale datasets difficult to curate.

Vendor:: XtelligentMedia Healthcare
Posted:: Jun 14, 2024
Published:: Jun 14, 2024
Format:: PDF
Type:: eGuide

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