148 lines
5.0 KiB
Python
148 lines
5.0 KiB
Python
import pydicom
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from pydicom.dataset import Dataset
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from pydicom.dataset import FileMetaDataset
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from pydicom.uid import MediaStorageDirectoryStorage, EncapsulatedPDFStorage, generate_uid
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import matplotlib.pyplot as plt
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from reportlab.pdfgen import canvas
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def load_mammography_image(dicom_path):
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"""Loads a mammography DICOM image as a NumPy array."""
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ds = pydicom.dcmread(dicom_path)
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image = ds.pixel_array
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return image, ds
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def extract_measurements(sr_path):
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"""Extracts measurement annotations from an SR DICOM file."""
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ds = pydicom.dcmread(sr_path)
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measurements = []
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probabilities = []
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if "ContentSequence" in ds:
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for itemLevel1 in ds.ContentSequence:
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if len(itemLevel1.ConceptNameCodeSequence) == 1:
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if itemLevel1.ConceptNameCodeSequence[0].CodeMeaning == "Imaging Measurements":
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for itemLevel2 in itemLevel1.ContentSequence:
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for itemLevel3 in itemLevel2.ContentSequence:
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if itemLevel3.ValueType == "SCOORD":
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measurements.append(itemLevel3.GraphicData)
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elif itemLevel3.ValueType == "NUM":
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if len(itemLevel3.MeasuredValueSequence) == 1:
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probabilities.append(itemLevel3.MeasuredValueSequence[0].NumericValue)
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return measurements, probabilities
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def overlay_measurements(image, measurements, probabilities):
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"""Overlays extracted measurements onto the mammography image."""
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fig, ax = plt.subplots()
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ax.imshow(image, cmap='gray')
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# Draw each polyline
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for i in range(0, len(measurements), 1):
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measurement = measurements[i]
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x = measurement[0::2] # Extract x-coordinates (every other value)
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y = measurement[1::2] # Extract y-coordinates (every other value)
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ax.plot(x, y, 'lime', linewidth=1) # Plot the entire polyline at once
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ax.text(x[-3] + 100, y[-3], f"{probabilities[i]:.2f} %", color='lime', fontsize=8)
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ax.axis("off")
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# Save the overlay as an image
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plt.savefig("temp.png", bbox_inches='tight', pad_inches=0)
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plt.close()
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def create_pdf(image_path, measurements, pdf_path):
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"""Creates a PDF with the mammography image and extracted measurements."""
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c = canvas.Canvas(pdf_path)
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# Add the image to the PDF
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c.drawImage(image_path, 50, 300)
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# Add extracted measurements
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c.setFont("Helvetica", 12)
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c.drawString(50, 280, "Extracted Measurements:")
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y = 260
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for text in measurements:
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c.drawString(70, y, f"- {text}")
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y -= 15 # Move down for each line
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c.save()
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def create_dcm_pdf(sr_path, pdf_path):
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sr = pydicom.dcmread(sr_path)
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ds = Dataset()
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# Add general DICOM metadata
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ds.PatientName = sr.PatientName
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ds.PatientID = sr.PatientID
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ds.PatientBirthDate = sr.PatientBirthDate
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ds.PatientSex = sr.PatientSex
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ds.StudyInstanceUID = sr.StudyInstanceUID
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ds.StudyDate = sr.StudyDate
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ds.StudyTime = sr.StudyTime
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ds.AccessionNumber = sr.AccessionNumber
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ds.ReferringPhysicianName = sr.ReferringPhysicianName
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ds.StudyID = sr.StudyID
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ds.SeriesInstanceUID = generate_uid()
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ds.SeriesDate = sr.SeriesDate
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ds.SeriesTime = sr.SeriesTime
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ds.SeriesNumber = 1
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ds.Modality = "DOC"
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ds.Manufacturer = "MammographyAI"
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ds.ConversionType = "DI"
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ds.SOPInstanceUID = generate_uid()
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ds.SOPClassUID = EncapsulatedPDFStorage
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# Open the PDF file and read it as binary data
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with open(pdf_path, 'rb') as f:
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pdf_data = f.read()
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# Add the EncapsulatedDocument (PDF content) to the DICOM dataset
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ds.ContentDate = ds.SeriesDate
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ds.ContentTime = ds.SeriesTime
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ds.AcquisitionDateTime = ""
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ds.InstanceNumber = 1
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ds.BurnedInAnnotation = "YES"
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ds.DocumentTitle = ""
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ds.EncapsulatedDocument = pdf_data
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ds.MIMETypeOfEncapsulatedDocument = "application/pdf"
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# Create a FileMetaDataset for DICOM file meta information
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file_meta = FileMetaDataset()
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file_meta.MediaStorageSOPClassUID = EncapsulatedPDFStorage
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file_meta.MediaStorageSOPInstanceUID = ds.SOPInstanceUID
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file_meta.TransferSyntaxUID = pydicom.uid.ImplicitVRLittleEndian
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file_meta.FileMetaInformationGroupLength = 0
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# Assign the file meta information to the dataset
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ds.file_meta = file_meta
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# Ensure preamble and "DICM" prefix is included
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ds.is_implicit_VR = True # Set to explicit VR
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ds.is_little_endian = True # Set to little endian
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# Save the DICOM file with the preamble and DICM prefix
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output_file = "output.dcm"
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ds.save_as(output_file, write_like_original=False)
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print(f"DICOM file created: {output_file}")
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test = pydicom.dcmread("output.dcm")
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print("test")
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# Example usage
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mammogram_path = "MG000001.dcm"
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sr_path = "SR000001.dcm"
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image, dicom_ds = load_mammography_image(mammogram_path)
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measurements, probabilities = extract_measurements(sr_path)
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overlay_measurements(image, measurements, probabilities)
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create_pdf("temp.png", measurements, "temp.pdf")
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create_dcm_pdf(sr_path, "temp.pdf",) |