src/FILE_UPLOAD_IMPLEMENTATION.md

File Upload Implementation for Medical Image Analyzer

Overview

The medical_image_analyzer now fully supports uploading files without extensions (like IM_0001), matching the vetdicomviewer implementation.

Key Implementation Details

1. Backend (medical_image_analyzer.py)

# Line 674 in process_file method
ds = pydicom.dcmread(file_path, force=True)

• Uses force=True parameter to read any file as DICOM first
• Falls back to regular image processing if DICOM reading fails
• No filename filtering - accepts all files

2. Frontend File Upload (wrapper_test.py & app.py)

file_input = gr.File(
    label="Select Medical Image File (.dcm, .dicom, IM_*, .png, .jpg, etc.)",
    file_count="single",
    type="filepath",
    elem_classes="file-upload"
    # Note: NO file_types parameter = accepts ALL files
)

• No file_types parameter means ALL files are accepted
• Clear labeling mentions "IM_*" files
• Custom CSS styling for better UX

3. Svelte Component (Index.svelte)

// Always try DICOM first for files without extensions
if (!file_ext || file_ext === 'dcm' || file_ext === 'dicom' || 
    file.type === 'application/dicom' || file.name.startsWith('IM_')) {
    // Process as DICOM
}

• Prioritizes DICOM processing for files without extensions
• Specifically checks for files starting with "IM_"

Features Added

1. ROI Visualization

• Draw ROI circle on the image
• Visual feedback for point analysis location
• Toggle to show/hide overlay

2. Fat Segmentation Overlay

• Display fat percentages on CT images
• Color-coded visualization (when masks available)
• Legend for subcutaneous vs visceral fat

3. Enhanced UI

• Two-tab view: Original Image | Overlay View
• File information display with metadata
• Improved text contrast and styling
• English interface (no German text)

Testing

Run the test script to verify IM_0001 support:

python test_im_files.py

Output confirms:

• ✅ IM_0001 files load successfully
• ✅ DICOM metadata extracted properly
• ✅ Analysis functions work correctly
• ✅ HU values calculated for CT images

File Type Support

1. DICOM files: .dcm, .dicom
2. Files without extensions: IM_0001, IM_0002, etc.
3. Regular images: .png, .jpg, .jpeg, .tiff, .bmp
4. Any other file: Will attempt DICOM first, then image

Usage Example

# Both wrapper_test.py and app.py now support:
# 1. Upload any medical image file
# 2. Automatic modality detection for DICOM
# 3. ROI visualization on demand
# 4. Fat segmentation info overlay

# The file upload is unrestricted:
# - Accepts ALL file types
# - Uses force=True for DICOM reading
# - Graceful fallback to image processing

Summary

The medical_image_analyzer now matches vetdicomviewer's file handling capabilities:

• ✅ Supports files without extensions (IM_0001)
• ✅ ROI visualization on images
• ✅ Fat segmentation overlay (text-based currently)
• ✅ Enhanced UI with better contrast
• ✅ English-only interface
• ✅ Synchronized app.py with wrapper_test.py features