# 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