{'fraction_non_alphanumeric': 0.014511873350923483, 'fraction_numerical': 0.0, 'mean_word_length': 5.432203389830509, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Analysis and improvement of image-based insertion point estimation for robot-assisted minimally invasive surgery

Estimating insertion points of surgical instruments for minimally invasive surgery is a necessary step to be able to control surgical instruments using endoscopic images. In this paper, we propose an analysis of possible methods which use image information only. Mathematical properties are detailed together with statistical properties obtained by simulations. Then a specific method is chosen to estimate the insertion point for bi-modal surgery (laparoscopy and flexible endoscopy). In vitro experiments show the accuracy of the approach and how it is possible to track the motion of the insertion point in the case of physiological motions.