Module iqsm_plus 

iQSM+ single-step deep-learning reconstruction (onnx feature).

iQSM+ (Gao 2024) extends iQSM with orientation-adaptive latent feature editing (OA-LFE): the B0 direction (z_prjs) is a network input, so oblique/sagittal/coronal acquisitions reconstruct correctly. The exported graph takes six inputs: phase, mask, te (s), b0 (T), z_prjs (B0 dir, [1,1,3]), and border (the LoT boundary mask, as for iQSM).

Pipeline (mirrors the authors’ inference.run_iqsm_plus): flip the phase sign, erode the mask by a radius-3 sphere, crop to the brain bounding box + 16-voxel margin, centre-pad to a multiple of 16, run, ×mask, then paste the result back into the full grid. Multi-echo data is combined with magnitude·TE² weighting.

Only axial-ish acquisitions are handled directly here; the authors’ extra axis-permutation for strongly oblique fields (|dir_y| > |dir_z|) is not applied.

Weights are not bundled; the caller passes the exported iqsm-plus.onnx bytes.

Functions

iqsm_plus

Run iQSM+ on a single echo of wrapped phase.

iqsm_plus_multi_echo

Multi-echo iQSM+: reconstruct each echo and combine with magnitude·TE² weights.

iqsm_plus_with 🔒