Created
October 1, 2017 12:10
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pylidc volume mask
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import pylidc as pl | |
import numpy as np | |
import matplotlib.pyplot as plt | |
from skimage.viewer import CollectionViewer | |
# Load scan, convert to volume. | |
scan = pl.query(pl.Scan).filter(pl.Scan.patient_id == "LIDC-IDRI-0001").first() | |
vol = scan.to_volume(verbose=False) | |
# mask_vol is a boolean, indicator volume for the first annotation of the scan. | |
mask_vol = np.zeros(vol.shape, dtype=np.bool) | |
# Load dicom files and obtain z-coords for each slice, so | |
# we can index into them. | |
dicoms = scan.load_all_dicom_images(verbose=False) | |
zs = [float(img.ImagePositionPatient[2]) for img in dicoms] | |
mask,bbox = scan.annotations[0].get_boolean_mask(return_bbox=True) | |
# Obtain indexes of `mask` into `mask_vol`. | |
i1,i2 = bbox[0].astype(np.int) | |
j1,j2 = bbox[1].astype(np.int) | |
k1 = zs.index(bbox[2,0]) | |
k2 = zs.index(bbox[2,1]) | |
mask_vol[i1:i2+1, j1:j2+1, k1:k2+1] = mask | |
# Send vol to range [0,1] for CollectionViewer. | |
vol = (vol-vol.min()) / (vol.max() - vol.min()) | |
# Gather slices augmented by mask_vol. | |
slices = [(mask_vol[:,:,i]*0.8+0.1)*vol[:,:,i] for i in range(vol.shape[2])] | |
# View them. | |
CollectionViewer(slices).show() |
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