Combining General and Domain-Specific Pretext Tasks for Brain MR Image Segmentation

arXiv:2609.30708 · cs.CV, cs.AI · Submitted 2026-09-25 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-09-25

Updated: 2026-09-25

Terminology

Fine-Tuning — 37× in this paper · explained in 5 episodes
Downstream Tasks — 11× in this paper · explained in 2 episodes
Transformer — 8× in this paper · explained in 2 episodes
Adam — 7× in this paper · explained in 2 episodes
Foundation Model — 6× in this paper · explained in 3 episodes
Self-Supervised Learning — 6× in this paper · explained in 8 episodes
Transferability — 5× in this paper · explained in 4 episodes
Foundation Models — 4× in this paper · explained in 7 episodes
Calgary Normative Study — 2× in this paper
Conference on Computer Vision and Pattern Recognition — 2× in this paper
Consistency — 2× in this paper · explained in 3 episodes
Transfer Learning — 2× in this paper · explained in 10 episodes
Ablation — 1× in this paper · explained in 1 episode
Ablation study — 1× in this paper · explained in 1 episode
Accuracy — 1× in this paper · explained in 1 episode
Benchmarking — 1× in this paper · explained in 4 episodes
Feature Extraction — 1× in this paper · explained in 2 episodes
Foundation Models (FMs) — 1× in this paper · explained in 2 episodes
Generalizability — 1× in this paper · explained in 6 episodes
Generalization — 1× in this paper · explained in 13 episodes
U-net architecture — 1× in this paper · explained in 3 episodes

Sources

Self-Supervised Pretext Tasks for Alzheimer's Disease Classification using 3D Convolutional Neural Networks on Large-Scale Synthetic Neuroimaging Dataset

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