| # Medical Imaging Dataset Validation Report | |
| **Date**: November 23, 2025 | |
| **Validation Tool Version**: 1.0 | |
| **Base Directory**: `/Users/dafesmith/Documents/repo/NeMo-agent/medical_ehr/data/imaging/` | |
| --- | |
| ## Executive Summary | |
| | Metric | Value | | |
| |--------|-------| | |
| | Total Datasets | 4 | | |
| | Total Files | 633 | | |
| | Valid Files | 620 | | |
| | Invalid Files | 13 | | |
| | Total Size | 385.38 MB | | |
| | Validation Rate | **97.95%** | | |
| --- | |
| ## Datasets Downloaded | |
| ### 1. Chest X-ray (Pneumonia Detection) | |
| | Property | Value | | |
| |----------|-------| | |
| | **Source** | HuggingFace: `hf-vision/chest-xray-pneumonia` | | |
| | **Location** | `chest_xray/pneumonia/` | | |
| | **Total Files** | 203 | | |
| | **Valid Files** | 203 (100%) | | |
| | **Total Size** | 313.03 MB | | |
| | **Image Format** | PNG | | |
| | **Image Resolution** | Variable (avg ~1500x1200 pixels) | | |
| **File Types**: | |
| - PNG images: 200 | |
| - JSON metadata: 2 | |
| - CSV labels: 1 | |
| **Label Distribution**: | |
| - Label 0 (Normal): 200 images | |
| **Sample Files**: | |
| - `0_00124.png` (1430x1128, 1.2 MB) | |
| - `0_00130.png` (1654x1368, 1.8 MB) | |
| - `0_00118.png` (1828x1511, 1.9 MB) | |
| --- | |
| ### 2. Brain MRI (Alzheimer Detection) | |
| | Property | Value | | |
| |----------|-------| | |
| | **Source** | HuggingFace: `Falah/Alzheimer_MRI` | | |
| | **Location** | `brain_mri/alzheimer/` | | |
| | **Total Files** | 203 | | |
| | **Valid Files** | 203 (100%) | | |
| | **Total Size** | 2.97 MB | | |
| | **Image Format** | PNG | | |
| | **Image Resolution** | 128x128 pixels | | |
| **File Types**: | |
| - PNG images: 200 | |
| - JSON metadata: 2 | |
| - CSV labels: 1 | |
| **Label Distribution**: | |
| - Label 0 (Mild Demented): 29 images | |
| - Label 1 (Moderate Demented): 2 images | |
| - Label 2 (Non Demented): 102 images | |
| - Label 3 (Very Mild Demented): 67 images | |
| **Sample Files**: | |
| - `2_00007.png` (128x128, 14.7 KB) | |
| - `0_00118.png` (128x128, 14.7 KB) | |
| - `3_00070.png` (128x128, 16.6 KB) | |
| --- | |
| ### 3. Dermatology (Skin Cancer Classification) | |
| | Property | Value | | |
| |----------|-------| | |
| | **Source** | HuggingFace: `marmal88/skin_cancer` | | |
| | **Location** | `dermatology/skin_cancer/` | | |
| | **Total Files** | 203 | | |
| | **Valid Files** | 203 (100%) | | |
| | **Total Size** | 68.77 MB | | |
| | **Image Format** | PNG | | |
| | **Image Resolution** | 600x450 pixels | | |
| **File Types**: | |
| - PNG images: 200 | |
| - JSON metadata: 2 | |
| - CSV labels: 1 | |
| **Label Distribution**: | |
| - Actinic Keratoses: 200 images | |
| **Additional Metadata Fields**: | |
| - image_id, lesion_id, dx_type, age, sex, localization | |
| **Sample Files**: | |
| - `actinic_keratoses_00056.png` (600x450, 310 KB) | |
| - `actinic_keratoses_00042.png` (600x450, 392 KB) | |
| - `actinic_keratoses_00095.png` (600x450, 383 KB) | |
| --- | |
| ### 4. DICOM Samples (Multi-modality Test Files) | |
| | Property | Value | | |
| |----------|-------| | |
| | **Source** | PyDICOM GitHub Repository | | |
| | **Location** | `dicom_samples/` | | |
| | **Total Files** | 24 | | |
| | **Valid Files** | 11 (45.8%) | | |
| | **Invalid Files** | 13 | | |
| | **Total Size** | 0.60 MB | | |
| | **Format** | DICOM (.dcm) | | |
| **File Types**: | |
| - DICOM files: 23 | |
| - JSON metadata: 1 | |
| **Successfully Validated DICOM Files**: | |
| | Filename | Modality | Study Date | Size | | |
| |----------|----------|------------|------| | |
| | MR_small.dcm | MR | 20040826 | 9.6 KB | | |
| | MR_small_bigendian.dcm | MR | 20040826 | 9.7 KB | | |
| | MR_small_implicit.dcm | MR | 20040826 | 9.7 KB | | |
| | MR_small_RLE.dcm | MR | 20040826 | 7.8 KB | | |
| | MR_small_expb.dcm | MR | 20040826 | 9.8 KB | | |
| | CT_small.dcm | CT | - | 39.7 KB | | |
| | ExplVR_BigEnd.dcm | - | - | 15.4 KB | | |
| | VR-2022.dcm | - | - | 258 KB | | |
| | J2K_pixelrep_mismatch.dcm | - | - | 138.5 KB | | |
| **Files with Validation Issues** (codec/format issues, not corruption): | |
| - JPEG Extended transfer syntax (requires specific codecs) | |
| - JPEG-LS files (requires pyjpegls or GDCM) | |
| - Files without DICM header (legacy format) | |
| - JPEG2000 with bit depth issues | |
| --- | |
| ## Directory Structure | |
| ``` | |
| /Users/dafesmith/Documents/repo/NeMo-agent/medical_ehr/data/imaging/ | |
| ├── brain_mri/ | |
| │ └── alzheimer/ | |
| │ ├── images/ (200 PNG files) | |
| │ └── metadata/ (labels.csv, labels.json, summary.json) | |
| ├── chest_xray/ | |
| │ ├── images/ (empty - not used) | |
| │ ├── metadata/ (empty - not used) | |
| │ └── pneumonia/ | |
| │ ├── images/ (200 PNG files) | |
| │ └── metadata/ (labels.csv, labels.json, summary.json) | |
| ├── ct_scans/ | |
| │ └── lidc_idri/ (empty - requires TCIA download) | |
| ├── dermatology/ | |
| │ └── skin_cancer/ | |
| │ ├── images/ (200 PNG files) | |
| │ └── metadata/ (labels.csv, labels.json, summary.json) | |
| ├── dicom_samples/ | |
| │ ├── brainix/ (empty - requires premium access) | |
| │ ├── manix/ (empty - requires premium access) | |
| │ └── *.dcm (23 DICOM test files) | |
| ├── medical_docs/ | |
| │ └── ocr_samples/ (empty - future use) | |
| ├── download_medical_imaging.py | |
| ├── download_chest_xray.py | |
| ├── validate_datasets.py | |
| ├── download_summary.json | |
| ├── validation_results.json | |
| └── validation_report.md (this file) | |
| ``` | |
| --- | |
| ## Issues Encountered | |
| ### 1. HuggingFace Dataset Script Deprecation | |
| **Issue**: The original `alkzar90/NIH-Chest-X-ray-dataset` uses deprecated dataset scripts. | |
| **Error**: `RuntimeError: Dataset scripts are no longer supported` | |
| **Resolution**: Used alternative dataset `hf-vision/chest-xray-pneumonia` with modern Parquet format. | |
| ### 2. OsiriX DICOM Library Access | |
| **Issue**: OsiriX sample datasets (BRAINIX, MANIX) require premium membership. | |
| **Resolution**: Downloaded alternative DICOM test files from PyDICOM GitHub repository. | |
| ### 3. DICOM Codec Dependencies | |
| **Issue**: Some DICOM files require specialized codecs (JPEG-LS, GDCM) for pixel data extraction. | |
| **Error Types**: | |
| - "JPEG Extended only supported by Pillow if Bits Allocated = 8" | |
| - "Missing required dependencies: GDCM, pyjpegls" | |
| **Resolution**: Files are valid DICOM, but pixel data extraction requires additional libraries. For testing purposes, the available files with standard transfer syntaxes are sufficient. | |
| ### 4. Kaggle CLI Not Available | |
| **Issue**: Kaggle CLI not installed, preventing direct NIH Chest X-ray dataset download. | |
| **Resolution**: Used HuggingFace as primary source. | |
| --- | |
| ## Validation Details | |
| ### Image Validation Checks | |
| 1. **File Integrity**: PIL Image.verify() for PNG/JPG files | |
| 2. **Format Verification**: Confirmed PNG format and RGB mode | |
| 3. **Size Measurement**: File size and image dimensions | |
| 4. **Metadata Presence**: Checked for labels.csv and labels.json | |
| ### DICOM Validation Checks | |
| 1. **DICM Magic Number**: Checked for DICOM preamble | |
| 2. **Metadata Extraction**: Patient ID (anonymized), Modality, Study Date | |
| 3. **Pixel Data**: Attempted pixel array extraction where possible | |
| --- | |
| ## Recommendations | |
| ### Immediate Next Steps | |
| 1. **Install DICOM Codecs** (optional): | |
| ```bash | |
| pip install pylibjpeg pylibjpeg-libjpeg pyjpegls | |
| ``` | |
| 2. **Download More Chest X-rays**: Current sample has limited label diversity (all label 0). Consider downloading balanced dataset. | |
| 3. **Add CT Scan Data**: LIDC-IDRI requires TCIA Data Retriever. Alternative: use Stanford AIMI datasets. | |
| ### For Production Use | |
| 1. **PhysioNet Credentialing**: Register for MIMIC-CXR access (224,316 chest X-rays) | |
| 2. **TCIA Registration**: Access LIDC-IDRI (1,018 CT scans with annotations) | |
| 3. **VinDr-CXR**: Consider Vietnamese chest X-ray dataset (18,000 images) | |
| ### Data Augmentation | |
| Consider augmenting the current datasets: | |
| - Random rotations, flips, brightness adjustments for training | |
| - Resize consistency (all images to standard size like 224x224) | |
| --- | |
| ## Files Created | |
| | File | Purpose | Size | | |
| |------|---------|------| | |
| | `download_medical_imaging.py` | Main download script | 6 KB | | |
| | `download_chest_xray.py` | ChestX-ray14 download (legacy) | 3 KB | | |
| | `validate_datasets.py` | Validation script | 6 KB | | |
| | `download_summary.json` | Download metadata | 1 KB | | |
| | `validation_results.json` | Detailed validation output | 11 KB | | |
| | `validation_report.md` | This report | 8 KB | | |
| --- | |
| ## Appendix: Dataset Sources | |
| | Dataset | Source | License | Registration Required | | |
| |---------|--------|---------|----------------------| | |
| | Chest X-ray Pneumonia | HuggingFace | CC0 | No | | |
| | Alzheimer MRI | HuggingFace | Unknown | No | | |
| | Skin Cancer | HuggingFace | CC BY-NC-SA 4.0 | No | | |
| | DICOM Samples | PyDICOM | MIT | No | | |
| | LIDC-IDRI | TCIA | CC BY 3.0 | Yes (TCIA) | | |
| | MIMIC-CXR | PhysioNet | PhysioNet | Yes (PhysioNet) | | |
| | OsiriX Samples | OsiriX | Premium | Yes (Paid) | | |
| --- | |
| **Report Generated**: 2025-11-23T13:37:06 | |
| **Validation Script**: validate_datasets.py | |
| **Download Script**: download_medical_imaging.py | |