SpineNetV2: Automated Detection, Labelling and Radiological Grading Of Clinical MR Scans

3 May 2022 · Rhydian Windsor, Amir Jamaludin, Timor Kadir, Andrew Zisserman ·

This technical report presents SpineNetV2, an automated tool which: (i) detects and labels vertebral bodies in clinical spinal magnetic resonance (MR) scans across a range of commonly used sequences; and (ii) performs radiological grading of lumbar intervertebral discs in T2-weighted scans for a range of common degenerative changes. SpineNetV2 improves over the original SpineNet software in two ways: (1) The vertebral body detection stage is significantly faster, more accurate and works across a range of fields-of-view (as opposed to just lumbar scans). (2) Radiological grading adopts a more powerful architecture, adding several new grading schemes without loss in performance. A demo of the software is available at the project website: http://zeus.robots.ox.ac.uk/spinenet2/.

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Body Detection

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1x1 Convolution • Batch Normalization • Bottleneck Residual Block • Convolution • ReLU • Residual Block • Residual Connection • Sigmoid Activation • SpineNet • Swish

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SpineNetV2: Automated Detection, Labelling and Radiological Grading Of Clinical MR Scans

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