To address the challenge of traditional ultrasound imaging in distinguishing low-contrast damaged areas after thermal ablation therapy, the system integrates ultrasound RF data, tissue attenuation coefficients, and Nakagami parameters to achieve automatic feature extraction and artificial features via a CNN deep learning model, which enhanced recognition accuracy. It enables real-time, precise monitoring of thermal ablation zones for breast cancer, prostate cancer, overcoming the limitations of traditional ultrasound after bubble dissipation and providing reliable intraoperative evaluation for in situ tumor treatment.

Technology provider:Xi'an Jiaotong University