From Macro to Micro: Autonomous Multiscale Image Fusion for Robotic Surgery

Minimally invasive surgery (MIS), performed through a small number of keyhole incisions, has become the standard of care for many general surgical procedures, reducing trauma, blood loss, and other complications and offering patients the prospect of a faster recovery with less postoperative pain. These improvements for the patient, however, require higher dexterity and complex instrument control by the surgeons. Keyhole incisions constrain the motion of surgical instruments, while the loss of stereovision when using a laparoscope or endoscope means that depth perception is much poorer than in traditional open surgery. The desire to tackle these issues has been the main driver behind the development of robotic MIS systems with stereovision. In particular, the da Vinci robot (Intuitive Surgical, Inc., Sunnyvale, California) is a successful surgical platform, used widely in the treatment of gynecological and urological cancers. While human guidance is essential for MIS, recent studies [1] have suggested that automation of some surgical subtasks, particularly those that are tedious and repetitive or require high precision, can be beneficial in improving accuracy and reducing the cognitive load of the surgeon. For example, several studies have investigated automation of surgical suturing subtasks, including using a suturing tool under fluorescence guidance [2], and other studies have explored areas such as autonomous tissue dissection [3].