A convolutional approach to vertebrae detection and labelling in whole spine MRI
We propose a novel convolutional method for the detection and identification of vertebrae in whole spine MRIs. This involves using a learnt vector field to group detected vertebrae corners together into individual vertebral bodies and convolutional image-to-image translation followed by beam search...
| 主要な著者: | , , , |
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| フォーマット: | Conference item |
| 言語: | English |
| 出版事項: |
Springer
2020
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| _version_ | 1826286489371148288 |
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| author | Windsor, R Jamaludin, A Kadir, T Zisserman, A |
| author_facet | Windsor, R Jamaludin, A Kadir, T Zisserman, A |
| author_sort | Windsor, R |
| collection | OXFORD |
| description | We propose a novel convolutional method for the detection and identification of vertebrae in whole spine MRIs. This involves using a learnt vector field to group detected vertebrae corners together into individual vertebral bodies and convolutional image-to-image translation followed by beam search to label vertebral levels in a self-consistent manner. The method can be applied without modification to lumbar, cervical and thoracic-only scans across a range of different MR sequences. The resulting system achieves 98.1% detection rate and 96.5% identification rate on a challenging clinical dataset of whole spine scans and matches or exceeds the performance of previous systems of detecting and labelling vertebrae in lumbar-only scans. Finally, we demonstrate the clinical applicability of this method, using it for automated scoliosis detection in both lumbar and whole spine MR scans. |
| first_indexed | 2024-03-07T01:44:31Z |
| format | Conference item |
| id | oxford-uuid:97f7f681-0121-4dcc-8511-78cfccd205cc |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T01:44:31Z |
| publishDate | 2020 |
| publisher | Springer |
| record_format | dspace |
| spelling | oxford-uuid:97f7f681-0121-4dcc-8511-78cfccd205cc2022-03-27T00:03:38ZA convolutional approach to vertebrae detection and labelling in whole spine MRIConference itemhttp://purl.org/coar/resource_type/c_5794uuid:97f7f681-0121-4dcc-8511-78cfccd205ccEnglishSymplectic ElementsSpringer2020Windsor, RJamaludin, AKadir, TZisserman, AWe propose a novel convolutional method for the detection and identification of vertebrae in whole spine MRIs. This involves using a learnt vector field to group detected vertebrae corners together into individual vertebral bodies and convolutional image-to-image translation followed by beam search to label vertebral levels in a self-consistent manner. The method can be applied without modification to lumbar, cervical and thoracic-only scans across a range of different MR sequences. The resulting system achieves 98.1% detection rate and 96.5% identification rate on a challenging clinical dataset of whole spine scans and matches or exceeds the performance of previous systems of detecting and labelling vertebrae in lumbar-only scans. Finally, we demonstrate the clinical applicability of this method, using it for automated scoliosis detection in both lumbar and whole spine MR scans. |
| spellingShingle | Windsor, R Jamaludin, A Kadir, T Zisserman, A A convolutional approach to vertebrae detection and labelling in whole spine MRI |
| title | A convolutional approach to vertebrae detection and labelling in whole spine MRI |
| title_full | A convolutional approach to vertebrae detection and labelling in whole spine MRI |
| title_fullStr | A convolutional approach to vertebrae detection and labelling in whole spine MRI |
| title_full_unstemmed | A convolutional approach to vertebrae detection and labelling in whole spine MRI |
| title_short | A convolutional approach to vertebrae detection and labelling in whole spine MRI |
| title_sort | convolutional approach to vertebrae detection and labelling in whole spine mri |
| work_keys_str_mv | AT windsorr aconvolutionalapproachtovertebraedetectionandlabellinginwholespinemri AT jamaludina aconvolutionalapproachtovertebraedetectionandlabellinginwholespinemri AT kadirt aconvolutionalapproachtovertebraedetectionandlabellinginwholespinemri AT zissermana aconvolutionalapproachtovertebraedetectionandlabellinginwholespinemri AT windsorr convolutionalapproachtovertebraedetectionandlabellinginwholespinemri AT jamaludina convolutionalapproachtovertebraedetectionandlabellinginwholespinemri AT kadirt convolutionalapproachtovertebraedetectionandlabellinginwholespinemri AT zissermana convolutionalapproachtovertebraedetectionandlabellinginwholespinemri |