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Keywords: 3‑D medical image segmentation, multi‑scale learning, spectral attention, morphological priors, deep neural networks.
| Item | Value | |------|-------| | Input resolution | 128 × 128 × 128 (isotropic) | | Batch size | 2 (GPU memory‑limited) | | Optimizer | AdamW (lr = 1e‑4, weight decay = 1e‑5) | | Scheduler | Cosine annealing with warm‑up (5 epochs) | | Training epochs | 200 | | Framework | PyTorch 2.0 + TorchIO for data augmentation | | Augmentations | Random elastic deformations, intensity scaling, bias field, Gaussian noise | mism-233
All components are differentiable and trained jointly. Keywords: 3‑D medical image segmentation
I’m unable to find any verified or widely recognized information about “mism-233.” It does not correspond to a known standard, product code, academic course, technical specification, or common reference in public databases. or common reference in public databases.