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Multiple_sclerosis_lesion_tracker

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kstember commited on Nov 13, 2025

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3805678

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1 Parent(s): cddb718

Update app.py

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app.py +11 -344

app.py CHANGED Viewed

@@ -12,8 +12,6 @@ import SimpleITK as sitk
 from huggingface_hub import hf_hub_download
 import spaces
-from pathlib import Path
-from typing import Optional, Dict
 # Dummy function to satisfy HF Spaces GPU detection during startup
@@ -68,6 +66,7 @@ try:
 except Exception:
     pass
 def is_zip(path: Path) -> bool:
     return path.suffix.lower() == ".zip"
@@ -297,7 +296,8 @@ def register_rigid_affine(prev_stripped: Path, new_stripped: Path, reg_dir: Path
     sitk.WriteImage(registered_img, str(registered_path))
     return registered_path, affine_tx, fixed
-@spaces.GPU(duration=300)
 def run_flames_single(input_nii: Path, out_mask_path: Path, device: str = "cuda") -> Path:
     """Run FLAMeS (nnUNetv2) on a single input NIfTI and write a mask. Uses shared MODEL_ROOT."""
     with (Path(input_nii).open("rb")):
@@ -498,321 +498,6 @@ def package_selected(job_dir: Path,
 # =========================
-# NiiVue viewer (HTML iframe) — uses /jobs/<relative path>
-# =========================
-from pathlib import Path
-from typing import Optional, Dict
-import json
-def niivue_iframe_for(
-    abs_fs_path: Path,
-    overlay_abs_fs_paths: Optional[Dict[str, Path]] = None,
-    default_overlay_key: Optional[str] = "New lesions only",
-) -> str:
-    """
-    Creates a standalone HTML file with NiiVue that embeds file paths.
-    The HTML uses absolute /file= URLs that work in HF Spaces.
-    """
-    base_path = Path(abs_fs_path).resolve()
-    # Find job directory (go up from registered_dir)
-    job_dir = base_path.parent
-    while job_dir.name in ["registered", "stripped", "seg_flames", "diff_seg"]:
-        job_dir = job_dir.parent
-    viewer_html = job_dir / "niivue_viewer.html"
-    # Build file URLs - these need to be absolute paths for Gradio
-    def make_file_url(p: Path) -> str:
-        return f"/file={p.resolve()}"
-    base_url = make_file_url(base_path)
-    overlay_map = {}
-    if overlay_abs_fs_paths:
-        for label, p in overlay_abs_fs_paths.items():
-            overlay_map[label] = make_file_url(Path(p))
-    # Create standalone HTML with embedded URLs
-    html_content = f"""<!DOCTYPE html>
-<html lang="en">
-<head>
-  <meta charset="UTF-8">
-  <meta name="viewport" content="width=device-width, initial-scale=1.0">
-  <title>NiiVue Viewer</title>
-  <style>
-    * {{ margin: 0; padding: 0; box-sizing: border-box; }}
-    html, body {{
-      height: 100%;
-      background: #111;
-      color: #ddd;
-      font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, sans-serif;
-      overflow: hidden;
-    }}
-    #app {{
-      height: 100%;
-      display: flex;
-      flex-direction: column;
-    }}
-    #toolbar {{
-      flex: 0 0 auto;
-      display: flex;
-      flex-wrap: wrap;
-      gap: 12px;
-      align-items: center;
-      padding: 10px;
-      background: #1a1a1a;
-      border-bottom: 1px solid #333;
-    }}
-    #toolbar label {{
-      display: flex;
-      align-items: center;
-      gap: 6px;
-      font-size: 14px;
-    }}
-    select, input[type="range"] {{
-      background: #222;
-      color: #ddd;
-      border: 1px solid #444;
-      border-radius: 6px;
-      padding: 6px 10px;
-      font-size: 14px;
-    }}
-    select:focus, input:focus {{
-      outline: 2px solid #4cafef;
-      outline-offset: 2px;
-    }}
-    #status {{
-      margin-left: auto;
-      font-size: 13px;
-      opacity: 0.8;
-    }}
-    #canvas-container {{
-      flex: 1;
-      min-height: 0;
-      position: relative;
-    }}
-    #gl {{
-      width: 100%;
-      height: 100%;
-      display: block;
-    }}
-  </style>
-</head>
-<body>
-  <div id="app">
-    <div id="toolbar">
-      <label>
-        View:
-        <select id="view-select">
-          <option value="multiplanar" selected>Multi-planar</option>
-          <option value="axial">Axial</option>
-          <option value="coronal">Coronal</option>
-          <option value="sagittal">Sagittal</option>
-          <option value="render">3D Render</option>
-        </select>
-      </label>
-      <label>
-        Convention:
-        <select id="convention-select">
-          <option value="radiological" selected>Radiological (L→R)</option>
-          <option value="neurological">Neurological (R→R)</option>
-        </select>
-      </label>
-      <label>
-        Overlay:
-        <select id="overlay-select">
-          <option value="">None</option>
-        </select>
-      </label>
-      <label>
-        Opacity:
-        <input type="range" id="opacity-slider" min="0" max="100" value="60">
-        <span id="opacity-value">60%</span>
-      </label>
-      <label>
-        Colormap:
-        <select id="colormap-select">
-          <option value="actc" selected>ACTC</option>
-          <option value="jet">Jet</option>
-          <option value="hot">Hot</option>
-          <option value="cool">Cool</option>
-          <option value="viridis">Viridis</option>
-          <option value="roi">ROI</option>
-        </select>
-      </label>
-      <span id="status">Loading...</span>
-    </div>
-    <div id="canvas-container">
-      <canvas id="gl"></canvas>
-    </div>
-  </div>
-  <script type="module">
-    // Embedded configuration
-    const CONFIG = {{
-      baseUrl: {json.dumps(base_url)},
-      overlays: {json.dumps(overlay_map)},
-      defaultOverlay: {json.dumps(default_overlay_key)}
-    }};
-    console.log('NiiVue Config:', CONFIG);
-    // Import NiiVue
-    const {{ Niivue }} = await import('https://unpkg.com/@niivue/niivue@0.62.1/dist/index.js');
-    // Initialize
-    const statusEl = document.getElementById('status');
-    const nv = new Niivue({{
-      colorbarVisible: true,
-      crosshairWidth: 1,
-      backColor: [0.067, 0.067, 0.067, 1]
-    }});
-    await nv.attachTo('gl');
-    nv.setRadiologicalConvention(true);
-    function updateStatus(msg, isError = false) {{
-      statusEl.textContent = msg;
-      statusEl.style.color = isError ? '#ff6b6b' : '#ddd';
-    }}
-    // Load main volume
-    try {{
-      updateStatus('Loading MRI...');
-      console.log('Loading base from:', CONFIG.baseUrl);
-      await nv.loadVolumes([{{
-        url: CONFIG.baseUrl,
-        name: 'Registered MRI'
-      }}]);
-      updateStatus('MRI loaded ✓');
-      console.log('Base volume loaded successfully');
-    }} catch (err) {{
-      console.error('Failed to load base volume:', err);
-      updateStatus('Failed to load MRI: ' + err.message, true);
-    }}
-    // Populate overlay dropdown
-    const overlaySelect = document.getElementById('overlay-select');
-    for (const [label, url] of Object.entries(CONFIG.overlays)) {{
-      const option = document.createElement('option');
-      option.value = url;
-      option.textContent = label;
-      overlaySelect.appendChild(option);
-    }}
-    // Set default overlay
-    if (CONFIG.defaultOverlay && CONFIG.overlays[CONFIG.defaultOverlay]) {{
-      overlaySelect.value = CONFIG.overlays[CONFIG.defaultOverlay];
-    }}
-    // Overlay controls
-    async function loadOverlay(url, label) {{
-      if (!url) {{
-        // Remove all overlays
-        while (nv.volumes.length > 1) {{
-          nv.removeVolume(nv.volumes[nv.volumes.length - 1].id);
-        }}
-        updateStatus('MRI only');
-        nv.updateGLVolume();
-        return;
-      }}
-      try {{
-        updateStatus('Loading overlay...');
-        console.log('Loading overlay from:', url);
-        // Remove existing overlays
-        while (nv.volumes.length > 1) {{
-          nv.removeVolume(nv.volumes[nv.volumes.length - 1].id);
-        }}
-        // Load new overlay
-        await nv.addVolumeFromUrl({{ url, name: label || 'Overlay' }});
-        // Apply styling
-        const overlayIdx = nv.volumes.length - 1;
-        const opacity = parseInt(document.getElementById('opacity-slider').value) / 100;
-        nv.setOpacity(overlayIdx, opacity);
-        const colormap = document.getElementById('colormap-select').value;
-        nv.setColormap(nv.volumes[overlayIdx].id, colormap);
-        updateStatus('Overlay loaded ✓');
-        console.log('Overlay loaded successfully');
-      }} catch (err) {{
-        console.error('Failed to load overlay:', err);
-        updateStatus('Overlay failed: ' + err.message, true);
-      }}
-    }}
-    // Event listeners
-    overlaySelect.addEventListener('change', (e) => {{
-      const url = e.target.value;
-      const label = e.target.options[e.target.selectedIndex].text;
-      loadOverlay(url, label);
-    }});
-    document.getElementById('opacity-slider').addEventListener('input', (e) => {{
-      const val = e.target.value;
-      document.getElementById('opacity-value').textContent = val + '%';
-      if (nv.volumes.length > 1) {{
-        nv.setOpacity(1, val / 100);
-      }}
-    }});
-    document.getElementById('colormap-select').addEventListener('change', (e) => {{
-      if (nv.volumes.length > 1) {{
-        nv.setColormap(nv.volumes[1].id, e.target.value);
-      }}
-    }});
-    document.getElementById('view-select').addEventListener('change', (e) => {{
-      const sliceTypes = {{
-        'multiplanar': nv.sliceTypeMultiplanar ?? 4,
-        'axial': nv.sliceTypeAxial ?? 0,
-        'coronal': nv.sliceTypeCoronal ?? 1,
-        'sagittal': nv.sliceTypeSagittal ?? 2,
-        'render': nv.sliceTypeRender ?? 3
-      }};
-      nv.setSliceType(sliceTypes[e.target.value]);
-    }});
-    document.getElementById('convention-select').addEventListener('change', (e) => {{
-      nv.setRadiologicalConvention(e.target.value === 'radiological');
-    }});
-    // Load default overlay if set
-    if (overlaySelect.value) {{
-      const label = overlaySelect.options[overlaySelect.selectedIndex].text;
-      setTimeout(() => loadOverlay(overlaySelect.value, label), 500);
-    }}
-    // Handle resize
-    window.addEventListener('resize', () => {{
-      nv.resizeListener?.();
-      nv.updateGLVolume();
-    }});
-  </script>
-</body>
-</html>"""
-    # Write HTML file
-    viewer_html.write_text(html_content, encoding='utf-8')
-    # Return iframe pointing to the HTML file
-    iframe_url = f"/file={viewer_html}"
-    return f'<iframe src="{iframe_url}" style="width:100%;height:85vh;border:none;border-radius:12px;background:#111;"></iframe>'
-#==========================
 # Main pipeline (UI callback)
 # =========================
 def _redact_paths(s: str) -> str:
@@ -822,19 +507,19 @@ def _redact_paths(s: str) -> str:
             s = s.replace(p, "[redacted]")
     return s
-@spaces.GPU(duration=300)
 def run_pipeline(file1, file2, dilate_prev_radius_vox=1, min_lesion_vol_ml=0.01):
     """
     file1: previous (baseline) FLAIR (.nii/.nii.gz or DICOM .zip)
     file2: new (follow-up) FLAIR (.nii/.nii.gz or DICOM .zip)
-    Returns: (status_html, outputs_zip_path_or_None, niivue_html_update, report_html_update)
     """
     if file1 is None or file2 is None:
         return (
             "<div>⚠️ Please upload both the previous and the new scan.</div>",
             None,
             gr.update(value="", visible=False),
-            gr.update(value="", visible=False),
         )
     ensure_dirs()
@@ -909,22 +594,6 @@ def run_pipeline(file1, file2, dilate_prev_radius_vox=1, min_lesion_vol_ml=0.01)
         if not outputs_zip.exists():
             raise RuntimeError("Packaging failed: outputs.zip not found.")
-        # Viewer overlays
-        overlay_paths: Dict[str, Path] = {
-            "All lesions (new scan)": new_mask_flames,
-            "New lesions only":       diff_paths["new_only"],
-            "Resolved lesions only":  diff_paths["resolved_only"],
-            "Stable overlap":         diff_paths["stable"],
-            "XOR diff":               diff_paths["xor"],
-            "Combined labels (1=stable, 2=new, 3=resolved)": diff_paths["combined"],
-        }
-        iframe_html = niivue_iframe_for(
-            registered_path,
-            overlay_abs_fs_paths=overlay_paths,
-            default_overlay_key="New lesions only"
-        )
         # Textual report
         report_html = f"""
         <div>
@@ -939,11 +608,10 @@ def run_pipeline(file1, file2, dilate_prev_radius_vox=1, min_lesion_vol_ml=0.01)
         </div>
         """.strip()
-        status_html = "✅ Done. Download the results below and explore them in the viewer."
         return (
             status_html,
             str(outputs_zip),
-            gr.update(value=iframe_html, visible=True),
             gr.update(value=report_html, visible=True),
         )
@@ -954,9 +622,9 @@ def run_pipeline(file1, file2, dilate_prev_radius_vox=1, min_lesion_vol_ml=0.01)
             status_html,
             None,
             gr.update(value="", visible=False),
-            gr.update(value="", visible=False),
         )
 # =========================
 # Gradio UI (refined, consistent theme)
 # =========================
@@ -1149,8 +817,8 @@ with gr.Blocks(
     <li>Upload <em>previous (baseline)</em> and <em>new (follow-up)</em>
         isotropic 3D FLAIR scans (<code>.nii/.nii.gz</code> or DICOM <code>.zip</code>).</li>
     <li>Click <strong>Run pipeline</strong>. Processing time takes approximately 3 minutes on current hardware.</li>
-    <li>The viewer will open with registered scan and highlighted new lesions.
-        Use the controls above the viewer to switch views, toggle orientation, and adjust overlay opacity/colormap.</li>
   </ul>
   <p style="margin-top:16px;"><strong>Advanced options:</strong></p>
@@ -1178,13 +846,12 @@ with gr.Blocks(
     status  = gr.HTML(label="Status", elem_id="status_box")
     out_zip = gr.File(label="Download outputs (ZIP)")
-    viewer  = gr.HTML(visible=False, label="Registered MRI viewer (with new-lesion overlay)")
     report  = gr.HTML(visible=False, label="Textual report", elem_id="report")
     run_btn.click(
         fn=run_pipeline,
         inputs=[prev_in, new_in, dil, minvol],
-        outputs=[status, out_zip, viewer, report]
     )
     # ----- References -----

 from huggingface_hub import hf_hub_download
 import spaces
 # Dummy function to satisfy HF Spaces GPU detection during startup
 except Exception:
     pass
 def is_zip(path: Path) -> bool:
     return path.suffix.lower() == ".zip"
     sitk.WriteImage(registered_img, str(registered_path))
     return registered_path, affine_tx, fixed
+@spaces.GPU(duration=500)
 def run_flames_single(input_nii: Path, out_mask_path: Path, device: str = "cuda") -> Path:
     """Run FLAMeS (nnUNetv2) on a single input NIfTI and write a mask. Uses shared MODEL_ROOT."""
     with (Path(input_nii).open("rb")):
 # =========================
 # Main pipeline (UI callback)
 # =========================
 def _redact_paths(s: str) -> str:
             s = s.replace(p, "[redacted]")
     return s
+@spaces.GPU(duration=500)
 def run_pipeline(file1, file2, dilate_prev_radius_vox=1, min_lesion_vol_ml=0.01):
     """
     file1: previous (baseline) FLAIR (.nii/.nii.gz or DICOM .zip)
     file2: new (follow-up) FLAIR (.nii/.nii.gz or DICOM .zip)
+    Returns: (status_html, outputs_zip_path_or_None, report_html_update)
     """
     if file1 is None or file2 is None:
         return (
             "<div>⚠️ Please upload both the previous and the new scan.</div>",
             None,
             gr.update(value="", visible=False),
         )
     ensure_dirs()
         if not outputs_zip.exists():
             raise RuntimeError("Packaging failed: outputs.zip not found.")
         # Textual report
         report_html = f"""
         <div>
         </div>
         """.strip()
+        status_html = "✅ Done. Download the results below to inspect them in your preferred viewer."
         return (
             status_html,
             str(outputs_zip),
             gr.update(value=report_html, visible=True),
         )
             status_html,
             None,
             gr.update(value="", visible=False),
         )
 # =========================
 # Gradio UI (refined, consistent theme)
 # =========================
     <li>Upload <em>previous (baseline)</em> and <em>new (follow-up)</em>
         isotropic 3D FLAIR scans (<code>.nii/.nii.gz</code> or DICOM <code>.zip</code>).</li>
     <li>Click <strong>Run pipeline</strong>. Processing time takes approximately 3 minutes on current hardware.</li>
+    <li>After processing, download the ZIP file and open the NIfTI outputs in your preferred neuroimaging viewer
+        (e.g. ITK-SNAP, FSLeyes, 3D Slicer) to inspect the lesions and overlays.</li>
   </ul>
   <p style="margin-top:16px;"><strong>Advanced options:</strong></p>
     status  = gr.HTML(label="Status", elem_id="status_box")
     out_zip = gr.File(label="Download outputs (ZIP)")
     report  = gr.HTML(visible=False, label="Textual report", elem_id="report")
     run_btn.click(
         fn=run_pipeline,
         inputs=[prev_in, new_in, dil, minvol],
+        outputs=[status, out_zip, report]
     )
     # ----- References -----