MRI-based surgical planning for lumbar spinal stenosis Conference Paper
| Authors: | Abbati, G.; Bauer, S.; Winklhofer, S.; Schüffler, P. J.; Held, U.; Burgstaller, J. M.; Steurer, J.; Buhmann, J. M. |
| Title: | MRI-based surgical planning for lumbar spinal stenosis |
| Conference Title: | 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2017) |
| Abstract: | The most common reason for spinal surgery in elderly patients is lumbar spinal stenosis (LSS). For LSS, treatment decisions based on clinical and radiological information as well as personal experience of the surgeon show large variance. Thus a standardized support system is of high value for a more objective and reproducible decision. In this work, we develop an automated algorithm to localize the stenosis causing the symptoms of the patient in magnetic resonance imaging (MRI). With 22 MRI features of each of five spinal levels of 321 patients, we show it is possible to predict the location of lesion triggering the symptoms. To support this hypothesis, we conduct an automated analysis of labeled and unlabeled MRI scans extracted from 788 patients. We confirm quantitatively the importance of radiological information and provide an algorithmic pipeline for working with raw MRI scans. Both code and data are provided for further research at www.spinalstenosis.ethz.ch. © Springer International Publishing AG 2017. |
| Keywords: | machine learning; lumbar spinal stenosis; deep learning |
| Journal Title | Lecture Notes in Computer Science |
| Volume: | 10435 |
| Conference Dates: | 2017 Sep 11-13 |
| Conference Location: | Quebec City, Canada |
| ISBN: | 0302-9743 |
| Publisher: | Springer |
| Date Published: | 2017-01-01 |
| Start Page: | 116 |
| End Page: | 124 |
| Language: | English |
| DOI: | 10.1007/978-3-319-66179-7_14 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Peter Schueffler's name is misspelled on the original publication -- In "20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part III" (ISBN: 978-3-319-66179-7) -- Conference Paper -- Export Date: 2 October 2017 -- Source: Scopus |
