USC scientists Amir Kalev and Naman Jain are exploring how quantum computing can improve cancer detection and treatment through medical imaging. Kalev, lead quantum scientist at USC Viterbi’s Information Sciences Institute, believes quantum computing could give physicians more accurate information when diagnosing cancer and planning treatment. Their research combines quantum computing with artificial intelligence to improve image segmentation, which traces a tumor’s exact outline pixel by pixel, separating cancerous from healthy tissue. More accurate boundaries could help doctors target radiation, plan surgery, and measure treatment effectiveness while reducing damage to nearby organs. The team created Quantum Feature Extraction, or QuFeX, a quantum module designed to strengthen existing AI systems. Their work was published in the journal “Quantum Science and Technology” in the paper “QuFeX: Quantum Feature Extraction Module for Hybrid Quantum-Classical Deep Neural Networks.” Jain, who earned a master’s degree in quantum information science in 2025, noted that medical datasets are small and often low quality, while traditional AI needs massive data to be reliable. The researchers wanted to see if quantum could close that gap. The work is still in its early stages, but the potential is enormous.