Name
Title | ||
|---|---|---|
A System For Augmented Reality Guided Laparoscopic Tumour Resection With Quantitative Ex-Vivo User Evaluation |
Abstract | ||
|---|---|---|
Augmented Reality (AR) guidance systems are currently being developed to help laparoscopic surgeons locate hidden structures such as tumours and major vessels. This can be achieved by registering pre-operative 3D data such as CT or MRI with the laparoscope's live video. For soft organs this is very challenging, and quantitative evaluation is both difficult and limited in the literature. It has been done previously by measuring registration accuracy using retrospective (non-live) data. However a performance evaluation of a real-time system in live use has not been presented. The clinical benefit has therefore not been measured. We describe an AR guidance system based on an existing one with several important improvements, that has been evaluated in an ex-vivo pre-clinical study for guiding tumour resections with porcine kidneys. The main improvement is a considerably better way to visually guide the surgeon, by showing them how to access the tumour with an incision tool. We call this Tool Access Visualisation. Performance was measured with the negative margin rate across 59 resected pseudo-tumours. This was 85.2% with AR guidance and 41.9% without, showing a very significant improvement (p = 0.0010, two-tailed Fisher's exact test). |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-54057-3_11 | COMPUTER-ASSISTED AND ROBOTIC ENDOSCOPY |
DocType | Volume | ISSN |
Conference | 10170 | 0302-9743 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Toby Collins | 1 | 57 | 7.10 |
| Pauline Chauvet | 2 | 0 | 0.34 |
| Clément Debize | 3 | 0 | 0.34 |
| Daniel Pizarro | 4 | 17 | 3.13 |
| Adrien Bartoli | 5 | 1147 | 89.14 |
| Michel Canis | 6 | 26 | 3.91 |
| Nicolas Bourdel | 7 | 0 | 0.34 |