Accept NRRD/MetaImage volumes via SimpleITK normalize-to-NIfTI

app.py

@@ -32,6 +32,7 @@ os.environ.setdefault("CONFIGS_ROOT", CKPT_DIR)
 
 import sys
 sys.path.insert(0, os.path.join(ROOT, "RADAR_inference"))  # vendored absolute imports (dynamic_network_architectures) resolve from here
+from intake import _to_nifti  # noqa: E402
 import pandas as pd  # noqa: E402
 import spaces  # noqa: E402
 import gradio as gr  # noqa: E402
@@ -77,22 +78,17 @@ def _english_name(column: str) -> str:
 def diagnose(ct_file):
     """Run RADAR on one uploaded contrast-enhanced abdominal CT volume."""
     path = ct_file if isinstance(ct_file, str) else ct_file.name
-    if not path.endswith((".nii", ".nii.gz")):
-        raise gr.Error("upload a .nii or .nii.gz CT volume")
-    try:
-        import nibabel as nib
-
-        nib.load(path)
-    except Exception:
-        raise gr.Error("upload a .nii or .nii.gz CT volume")
-
+    if path.lower().endswith(".dcm"):
+        raise gr.Error("a single .dcm is one slice, not a volume: upload the full series")
     tmpdir = tempfile.mkdtemp(prefix="radar_case_")
     outdir = tempfile.mkdtemp(prefix="radar_out_")
     try:
-        fname = os.path.basename(path)
-        if not fname.endswith((".nii", ".nii.gz")):
-            fname += ".nii.gz"
-        shutil.copy(path, os.path.join(tmpdir, fname))
+        src = _to_nifti(path, tmpdir)
+        fname = os.path.basename(src)
+        if src != os.path.join(tmpdir, fname):
+            if not fname.endswith((".nii", ".nii.gz")):
+                fname += ".nii.gz"
+            shutil.copy(src, os.path.join(tmpdir, fname))
         try:
             evaluate(pad_func, model, tmpdir, outdir, "space")
         except (OSError, ValueError, RuntimeError) as exc:
@@ -119,8 +115,8 @@ demo = gr.Interface(
     fn=diagnose,
     inputs=gr.File(
         # ".gz" not ".nii.gz": Gradio matches Path.suffix ("gz"), so the compound form never validates.
-        # diagnose() still enforces .nii/.nii.gz + NIfTI-parseable content server-side.
-        label="Abdominal CT (.nii.gz)", file_types=[".nii", ".gz"]
+        # diagnose() still enforces volume suffix + parseable content server-side.
+        label="Abdominal CT (NIfTI / NRRD / MetaImage)", file_types=[".nii", ".gz", ".nrrd", ".nhdr", ".mha", ".mhd"]
     ),
     outputs=[gr.Label(label="Top findings", num_top_classes=10), gr.Dataframe(label="All finding scores")],
     title="RADAR Abdominal CT",

intake.py

@@ -0,0 +1,38 @@
+"""Upload intake: normalize NIfTI / NRRD / MetaImage / DICOM series to .nii.gz.
+
+Downstream (RADAR_inference DataFolder/evaluate) only ever sees one .nii.gz,
+so the vendored upstream chain stays untouched. No new dependencies:
+SimpleITK and nibabel are already required.
+"""
+
+import os
+
+import gradio as gr
+
+VOLUME_SUFFIXES = (".nii", ".nii.gz", ".nrrd", ".nhdr", ".mha", ".mhd")
+
+
+def _to_nifti(path: str, workdir: str) -> str:
+    """Normalize one single-file volume to .nii.gz via SimpleITK."""
+    import SimpleITK as sitk
+
+    low = path.lower()
+    if low.endswith((".nii", ".nii.gz")):
+        import nibabel as nib
+
+        try:
+            nib.load(path)
+        except Exception:
+            raise gr.Error("upload a .nii or .nii.gz CT volume")
+        return path
+    if not low.endswith((".nrrd", ".nhdr", ".mha", ".mhd")):
+        raise gr.Error("upload a .nii.gz, .nrrd/.nhdr, .mha/.mhd volume, or a DICOM series")
+    try:
+        img = sitk.ReadImage(path)
+    except Exception:
+        raise gr.Error(f"could not read {os.path.basename(path)} as an image volume")
+    if img.GetDimension() != 3 or min(img.GetSize()) < 1:
+        raise gr.Error(f"{os.path.basename(path)} is not a 3D volume")
+    out = os.path.join(workdir, "case.nii.gz")
+    sitk.WriteImage(img, out)
+    return out