Document comprehensive logging features in batch processing

Update BATCH_PROCESSING_IMPLEMENTATION.md to highlight the detailed
logging system that helps verify the batch processing optimization
is working correctly.

Includes example log output showing:
- GPU detection and memory tracking
- Model loading phase with memory usage
- Per-slide processing with cache hit indicators
- Comprehensive batch summary with timing statistics

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

BATCH_PROCESSING_IMPLEMENTATION.md

@@ -74,6 +74,59 @@ Successfully implemented batch processing optimization for Mosaic slide analysis
 
 ## Key Features
 
+### ✅ Comprehensive Logging
+
+The batch processing system includes detailed logging to verify the optimization is working:
+
+**Model Loading Phase:**
+- GPU detection and total memory reporting
+- Memory usage before/after loading each model
+- Memory management strategy (T4 aggressive vs A100 caching)
+- Clear indication that models are loaded ONCE per batch
+
+**Slide Processing Phase:**
+- Per-slide progress indicators [n/total]
+- Confirmation that PRE-LOADED models are being used
+- Per-slide timing (individual and cumulative)
+- Paladin model cache hits vs new loads
+
+**Batch Summary:**
+- Total slides processed (success/failure counts)
+- Model loading time (done once for entire batch)
+- Total batch time and per-slide statistics (avg, min, max)
+- Batch overhead vs processing time breakdown
+- Optimization benefits summary
+
+**Example log output:**
+```
+================================================================================
+BATCH PROCESSING: Starting analysis of 10 slides
+================================================================================
+GPU detected: NVIDIA Tesla T4
+GPU total memory: 15.75 GB
+Memory management strategy: AGGRESSIVE (T4)
+✓ Marker Classifier loaded (GPU: 0.15 GB)
+✓ Aeon model loaded (GPU: 0.45 GB)
+✓ All core models loaded (Total: 0.45 GB)
+  These models will be REUSED for all slides in this batch
+Model loading completed in 3.2s
+
+[1/10] Processing: slide1.svs
+         Using pre-loaded models (no disk I/O for core models)
+  ✓ Using CACHED Paladin model: LUAD_EGFR.pkl (no disk I/O!)
+[1/10] ✓ Completed in 45.2s
+
+BATCH PROCESSING SUMMARY
+Total slides:        10
+Successfully processed: 10
+Model loading time:  3.2s (done ONCE for entire batch)
+Total batch time:    458.5s
+Per-slide times: Avg: 45.5s, Min: 42.1s, Max: 48.3s
+✓ Batch processing optimization benefits:
+  - Models loaded ONCE (not once per slide)
+  - Reduced disk I/O for model loading
+```
+
 ### ✅ Adaptive Memory Management
 
 **T4 GPUs (16GB memory)**: