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| import gradio as gr | |
| import numpy as np | |
| import polars as pl | |
| import pydicom | |
| from PIL import Image | |
| from pydicom.errors import InvalidDicomError | |
| def read_and_preprocess_dicom(file_path: str): | |
| """ | |
| Function to read and preprocess DICOM files | |
| :param file_path: Path to the DICOM file | |
| :return: Image data (in PIL format) and metadata (in pandas DataFrame format) | |
| """ | |
| try: | |
| # Read the DICOM file | |
| dicom_data = pydicom.dcmread(file_path) | |
| except InvalidDicomError: | |
| raise gr.Error("The uploaded file is not a valid DICOM file.") | |
| # Get the pixel data | |
| try: | |
| pixel_array = dicom_data.pixel_array | |
| except AttributeError: | |
| raise gr.Error("The uploaded DICOM file has no pixel data.") | |
| # Normalize the pixel data to 8-bit and convert to a PIL image | |
| if pixel_array.dtype != np.uint8: | |
| pixel_array = ((pixel_array - np.min(pixel_array)) / (np.max(pixel_array) - np.min(pixel_array)) * 255).astype( | |
| np.uint8) | |
| image = Image.fromarray(pixel_array) | |
| # Collect metadata in dictionary format and convert to DataFrame | |
| metadata_dict = {elem.name: str(elem.value) for elem in dicom_data.iterall() if elem.name != 'Pixel Data'} | |
| df_metadata = pl.DataFrame({ | |
| "Key": list(metadata_dict.keys()), | |
| "Value": list(metadata_dict.values()) | |
| }) | |
| return image, df_metadata.to_pandas() # Convert to pandas DataFrame for Gradio compatibility | |
| def build_interface(): | |
| """ | |
| Function to build the Gradio interface | |
| """ | |
| theme = gr.themes.Soft( | |
| primary_hue=gr.themes.colors.emerald, | |
| secondary_hue=gr.themes.colors.emerald | |
| ) | |
| with gr.Blocks(title='DICOM Viewer', theme=theme) as demo: | |
| gr.Markdown( | |
| """ | |
| # DICOM Viewer | |
| This app reads a DICOM file and displays the image and metadata. | |
| """ | |
| ) | |
| with gr.Column(): | |
| file_path = gr.File(label="Input DICOM Data") | |
| with gr.Row(): | |
| dicom_image = gr.Image(type="pil", label="DICOM Image") | |
| dicom_meta = gr.Dataframe(headers=None, label="Metadata") | |
| inputs = [file_path] | |
| outputs = [dicom_image, dicom_meta] | |
| file_path.upload(fn=read_and_preprocess_dicom, inputs=inputs, outputs=outputs) | |
| clear_button = gr.ClearButton(components=inputs + outputs, ) | |
| example = gr.Examples( | |
| ['assets/sample.dcm'], | |
| inputs=inputs, | |
| outputs=outputs, | |
| fn=read_and_preprocess_dicom, | |
| cache_examples=True | |
| ) | |
| return demo | |
| if __name__ == '__main__': | |
| demo = build_interface() | |
| demo.launch() | |