Create app.py

app.py

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+import gradio as gr
+import pydicom
+import numpy as np
+import matplotlib.pyplot as plt
+from monai.transforms import Compose, LoadImage, AddChannel, ScaleIntensity, ToTensor
+
+def interpret_dicom(files):
+    # files: list of uploaded DICOM files
+    slices = []
+    for file in files:
+        ds = pydicom.dcmread(file.name)
+        slices.append(ds.pixel_array)
+    # Sort slices if needed (for CT/MRI)
+    slices = np.array(slices)
+    # Simple visualization: show the middle slice
+    mid_slice = slices[len(slices)//2]
+    plt.imshow(mid_slice, cmap='gray')
+    plt.axis('off')
+    plt.title('Middle Slice')
+    plt.savefig('output.png')
+    plt.close()
+    # Here you would add MONAI model inference
+    # For now, just return the image
+    return 'output.png', "Interpretation: (placeholder)"
+
+iface = gr.Interface(
+    fn=interpret_dicom,
+    inputs=gr.File(file_count="multiple", label="Upload DICOM files"),
+    outputs=[gr.Image(type="filepath", label="Middle Slice"), gr.Textbox(label="Interpretation")],
+    title="DICOM Radiology Interpreter",
+    description="Upload your DICOM files (e.g., CT scan slices). The app will show the middle slice and provide an interpretation."
+)
+
+if __name__ == "__main__":
+    iface.launch()