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plt.imshow(patient6.windowed(l=100, w=700), cmap=plt.cm.bone);

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plt.imshow(patient6.windowed(*dicom_windows.mediastinum), cmap=plt.cm.bone);

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plt.imshow(patient6.windowed(*dicom_windows.lungs), cmap=plt.cm.bone);

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high_level = patient6.windowed(w=200, l=200)
low_level = patient6.windowed(w=200, l=-200)

show_images([high_level, low_level], titles=['high window level', 'low window level'], figsize=(7,7))

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high_width = patient6.windowed(w=1000, l=40)
low_width = patient6.windowed(w=100, l=40)

show_images([high_width, low_width], titles=['high window width', 'low window width'], figsize=(7,7))

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windowed_image = cropped.windowed(*dicom_windows.lungs)
show_image(windowed_image, cmap=plt.cm.bone);

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dfs = pd.DataFrame(windowed_image)
#uncomment below to view locally
#dfs.style.set_properties(**{'font-size':'6pt'}).background_gradient('bone').format("{:.1f}")

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df = pd.DataFrame(cropped)
#uncomment below to view locally
#df.style.set_properties(**{'font-size':'8pt'}).background_gradient('bone').format("{:.1f}")

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cropped = scaled[340:385,300:350]
show_image(cropped, cmap='bone');

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from fastai.vision.all import *
from fastai.medical.imaging import *

import matplotlib.pyplot as plt
plt.rcParams["figure.figsize"] = (7,7)

source = 'D:/Datasets/rsna_pulmonary'
files = get_dicom_files(source)
patient6 = files[6].dcmread()