Choroid plexus segmentation in MRI using the novel T1×FLAIR modality and PSU-Mamba: projective scan U-Mamba approach

Abstract

The Choroid Plexus (CP) is emerging as a biomarker for neurodegenerative diseases (NDDs) such as Alzheimer’s Disease and its precursor pathologies. However, segmentation remains challenging, especially without Contrast-Enhanced T1-weighted (CE-T1w) imaging which is invasive and rarely used in NDDs. To address these challenges, we present three key contributions. First, we propose and validate T1×FLAIR, a novel, non-invasive modality created by gamma-corrected voxelwise multiplication of coregistered T1w and FLAIR images. Expert visual inspection confirmed that this choice enhances CP visibility while preserving standard resolution. Second, we release ChP-MRI, a high-quality MRI dataset of 168 patients with NDDs or Multiple Sclerosis, including T1w, FLAIR, and T1×FLAIR images with expert-verified CP segmentations. The dataset is multi-pathology, and accompanied by demographic details to support benchmarking. Third, we propose PSU-Mamba (Projective Scan U-Mamba), an adaptation of the U-Mamba segmentation model where the first encoder block is a Mamba layer equipped with a PCA-based scan path derived from anatomical priors. This design enhances segmentation accuracy, maintains linear complexity, and converges faster with fewer training epochs. Experiments on ChP-MRI confirm that T1×FLAIR is a more faithful substitute for CE-T1w than T1w, and that PSU-Mamba offers systematic robustness in segmenting the CP. The source code and the dataset are available at https://github.com/phuselab/PSU_Mamba#.