Robust thalamic nuclei segmentation from T1-weighted MRI using polynomial intensity transformation

• Published in: Brain Structure and Function Vol. 229; no. 5; pp. 1087 - 1101
• Main Authors: Vidal, Julie P., Danet, Lola, Péran, Patrice, Pariente, Jérémie, Bach Cuadra, Meritxell, Zahr, Natalie M., Barbeau, Emmanuel J., Saranathan, Manojkumar
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2024; Springer Nature B.V; Springer Verlag
• Subjects: Adult; Biomedical and Life Sciences; Biomedicine; Cell Biology; Cognition; Female; Genetic transformation; Humans; Image processing; Image Processing, Computer-Assisted - methods; Life Sciences; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Male; Neural networks; Neural Networks, Computer; Neurology; Neurons and Cognition; Neurosciences; Original Article; Scanners; Segmentation; Thalamic nuclei; Thalamic Nuclei - diagnostic imaging; Thalamus; White Matter - diagnostic imaging; Thalamus; Thalamic nuclei segmentation; THOMAS; Structural imaging; structural imaging PHILIPS; thalamic nuclei segmentation
• ISSN: 1863-2661; 1863-2653; 1863-2661; 0340-2061
• DOI: 10.1007/s00429-024-02777-5

Accurate segmentation of thalamic nuclei, crucial for understanding their role in healthy cognition and in pathologies, is challenging to achieve on standard T1-weighted (T1w) magnetic resonance imaging (MRI) due to poor image contrast. White-matter-nulled (WMn) MRI sequences improve intrathalamic contrast but are not part of clinical protocols or extant databases. In this study, we introduce histogram-based polynomial synthesis (HIPS), a fast preprocessing transform step that synthesizes WMn-like image contrast from standard T1w MRI using a polynomial approximation for intensity transformation. HIPS was incorporated into THalamus Optimized Multi-Atlas Segmentation (THOMAS) pipeline, a method developed and optimized for WMn MRI. HIPS-THOMAS was compared to a convolutional neural network (CNN)-based segmentation method and THOMAS modified for the use of T1w images (T1w-THOMAS). The robustness and accuracy of the three methods were tested across different image contrasts (MPRAGE, SPGR, and MP2RAGE), scanner manufacturers (PHILIPS, GE, and Siemens), and field strengths (3 T and 7 T). HIPS-transformed images improved intra-thalamic contrast and thalamic boundaries, and HIPS-THOMAS yielded significantly higher mean Dice coefficients and reduced volume errors compared to both the CNN method and T1w-THOMAS. Finally, all three methods were compared using the frequently travelling human phantom MRI dataset for inter- and intra-scanner variability, with HIPS displaying the least inter-scanner variability and performing comparably with T1w-THOMAS for intra-scanner variability. In conclusion, our findings highlight the efficacy and robustness of HIPS in enhancing thalamic nuclei segmentation from standard T1w MRI.