Evaluation of suturing performance in general surgery and ocular microsurgery by combining computer vision-based software and distributed fiber optic strain sensors: a proof-of-concept.

Purpose: Improper suturing may cause an inadequate wound healing process and wound dehiscence as well as infection and even graft rejection in case of corneal transplantation. Hence, training surgeons in correct suturing procedures and objectively assessing their surgical skills is desirable.

Methods: Two complementary methods for assessment of suturing skills in two medical fields (general surgery and ocular microsurgery) were demonstrated.

Computerized model for objectively evaluating cutting performance using a laparoscopic box trainer simulator.

Background: Laparoscopic box trainer simulator has recently become a tool for assessment of physicians' surgical and laparoscopic skills, and training using such a simulator has been incorporated into the curricula of surgery syllabus. With the increased use of box trainer simulators, there is a great need for obtaining reliable and objective evaluations of the trainees' performances. Here, we introduce an automated tool for assessing laparoscopic cutting performance by using image-processing algorithms.