Fix inference pipeline: normalization, RAS orientation, state_dict check, debug logging

Add detailed logging for API requests to show in Hugging Face logs

Fix dimension mismatch: resample prediction mask to match original input dimensions

Fix critical issues: 50MB upload limit, report guardrails, T2 experimental status, API security, and indentation errors

Fix shape

Aggressive fixes: Higher T1 thresholds (0.60-0.80), stricter spatial priors, volume-based confidence penalty, reject <1000ml

Fix: Correct indentation errors and ensure PROCESSING_LOCK is threading.Lock()

Fix: Remove local ndimage imports that cause UnboundLocalError - use top-level import instead

Complete critical fixes: proper lock acquire/release, load NIfTI once, fix slice_idx bounds, remove redundant confidence check

Fix critical bugs: threading.Lock, NIfTI load once, z-axis calculations, confidence defaults, path guards

Added advanced guards

Fix confidence_score

Add T1 threshold 0.58, size-aware auto-tune, enhanced edge cleanup, centroid/Z-span guards, confidence score, remove emojis

Fix accuracy: match training preprocessing and use 0.5 threshold by default

Enhance medical report with detailed findings, clinical context, and quality assessment

Fix preprocessing, threshold, and post-processing for better predictions

Fix UnboundLocalError and Triton cache permission error

Production build strategy: Docker support, pinned dependencies, OOM guardrails, optimized defaults

Speed optimizations: GPU aggregation, max-autotune compile, increased batch/ROI, GPU utilization monitoring, quality guardrails

Add liver segmentation refinement pipeline: connected components, morphological cleanup, smoothing

Performance optimizations: warm-up, channels-last, TF32, GPU monitoring, memory-mapped I/O

Major performance and stability improvements: disable torch.compile by default, GPU preprocessing, ROI auto-adjustment, timeout mechanism, validation, cuDNN benchmarking, version logging, concurrency limits

Fix GPU OOM: Add post-load memory check, use ultra-minimal settings for low memory, and improve OOM recovery

Fix naming conflict: rename model.py to model_loader.py and initialize DEVICE to prevent NoneType errors

Refactor app.py into modular structure: config, model, processing, inference, and app modules