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Found 4 papers, 2 papers with code
Thalamic nuclei segmentation from T$_1$-weighted MRI: unifying and benchmarking state-of-the-art methods with young and old cohorts
The thalamus and its constituent nuclei are critical for a broad range of cognitive and sensorimotor processes, and implicated in many neurological and neurodegenerative conditions.
Robust thalamic nuclei segmentation from T1-weighted MRI
HIPS-THOMAS was compared to a convolutional neural network (CNN)-based segmentation method and THOMAS modified for T1w images (T1w-THOMAS).
A Contrast Synthesized Thalamic Nuclei Segmentation Scheme using Convolutional Neural Networks
The SCS network demonstrated a significant atrophy in Ventral lateral posterior nucleus in AUD patients compared to healthy age-matched controls (P=0. 01), agreeing with previous studies on thalamic atrophy in alcoholism, whereas the NCS network showed spurious atrophy of the Ventral posterior lateral nucleus.
Automated Thalamic Nuclei Segmentation Using Multi-Planar Cascaded Convolutional Neural Networks
For 7T WMn-MPRAGE, the proposed method outperforms current state-of-the-art on patients with ET with statistically significant improvements in Dice for five nuclei (increase in the range of 0. 05-0. 18) and VSI for four nuclei (increase in the range of 0. 05-0. 19), while performing comparably for healthy and MS subjects.
