Dear Colleagues,

Recent advances in medical imaging modalities and predictive computer simulations have dramatically changed current treatment models towards facilitating individualized surgical planning. Advanced machine learning and deep learning algorithms have become influential in the medical fields, and it may be important to expedite the incorporation of these innovative technologies into surgical planning.

Therefore, this Special Issue on “Deep learning and Medical Innovation in Minimally Invasive Surgery” will focus on original research papers and comprehensive reviews of cutting-edge experimental methodologies for investigating machine or deep learning in minimally invasive surgery (including laparoscopic, endoscopic, and robotic surgery). Topics of interest for this Special Issue include, but are not limited to:

Advanced machine learning techniques to aid in surgical planning, strategy, or perioperative management.
Novel deep learning models for surgical features, imaging, and process recognition.
The development of a deep learning algorithm for minimally invasive surgery.
The in vivo quantification of the functional properties of innovative devices for minimally invasive surgery.
The verification and validation of image-based deep learning algorithms in surgery.
Advanced computational biomechanics for rapid, personalized surgical simulation and preoperative treatment planning.
We will consider contributions from all fields of research, as long as experiments and predictive simulations are the main driving force of the research.

Dr. Chien-Hung Liao
Guest Editor