Automated subcortical volume estimation from 2D MRI in epilepsy and implications for clinical trials.
Daniel BrownhillYachin ChenBarbara A K KreilkampChristophe de BezenacChristine DenbyMartyn BracewellShubhabrata BiswasKumar DasAnthony G MarsonSimon S KellerPublished in: Neuroradiology (2021)
Automated subcortical volume estimation of 2D images with a resolution of 0.4 × 0.4x3mm using a modified FIRST pipeline is consistent with volumes derived from 3D images, although this consistency decreases with an increased slice thickness. Thalamic and putamen atrophy has previously been reported in patients with IGE. Automated subcortical volume estimation from 2D images is feasible and most reliable at using in-plane acquisitions greater than 1 mm x 1 mm and provides an opportunity to perform quantitative image analysis studies in clinical trials.
Keyphrases
- deep learning
- clinical trial
- convolutional neural network
- optical coherence tomography
- machine learning
- white matter
- high throughput
- magnetic resonance imaging
- high resolution
- contrast enhanced
- phase ii
- deep brain stimulation
- computed tomography
- randomized controlled trial
- mass spectrometry
- phase iii
- study protocol
- case control