Summary: Preoperative administration of indocyanine green (ICG) improves the detection of liver tumors in patients undergoing minimally invasive liver resection guided by conventional intraoperative ultrasound. The primary objectives of this study are to evaluate the efficacy of ICG fluorescence uptake in combination with intraoperative ultrasonography and preoperative magnetic resonance imaging for detecting liver tumors. Additionally, a machine-learning algorithm will be developed to enhance liver tumor detection using ICG through photographic analysis. Secondary objectives include investigating the distribution of ICG in liver tissue and its correlation with hepatic fibrosis and steatosis, as well as describing patterns of ICG uptake and their relationship with liver tumors. The study also aims to analyze various clinical outcomes such as the 30-day comprehensive complication index, operation time, conversion to open surgery rate, length of hospital stay, liver tumor recurrence, readmission rate, complications, and 90-day mortality. This research seeks to advance tumor detection methods and improve patient outcomes in minimally invasive liver resection procedures.