This review presents a comprehensive overview of recent advancements and clinical applications of three-dimensional (3D) reconstruction technology in thoracic surgery, with a focus on lung cancer surgery. The widespread adoption of chest computed tomography (CT) screening has increased the detection rates of early-stage lung cancers, facilitating a transition from traditional lobectomy to parenchymal-sparing sublobar resections, such as segmentectomy, which demand higher anatomical precision. 3D reconstruction technology significantly improves tumor localization, as well as vascular and bronchial visualization, thereby enhancing surgical accuracy and safety. Its key applications encompass preoperative planning, intraoperative navigation, real-time localization, vascular and airway visualization, and postoperative pulmonary function assessment, collectively contributing to improved surgical outcomes and patient prognosis. Recent innovations in artificial intelligence have streamlined and automated the reconstruction process, leading to reduced operative times and increased accuracy. However, challenges persist, including image quality limitations, algorithm robustness, and limited high-quality clinical evidence. Future integration with emerging technologies such as virtual reality and augmented reality holds promise for achieving personalized, intelligent thoracic surgical procedures. This review aims to systematically evaluate the clinical value of 3D reconstruction technology and explore its future development directions.