from SegmentationFunctions import *
def modelPipeline(img_path):
ID = img_path[img_path.find('/') + 1 : img_path.find('_')]
sliceNo = img_path[img_path.find('_') + 1 : img_path.find('.')]
print('\t******* SEGMENTATION PIPELINE ********')
print('Patient:', ID + ', Slice Number:', sliceNo)
im = readImg(img_path, showOutput=0)
procImg, fg_threshold = preprocessImage(im, showOutput=0)
print('...preprocessing')
fg_mask = getForegroundMask(procImg, fg_threshold, showOutput=0)
print('...computing foreground mask')
trachea_mask, lung_mask, ch_lung_mask, int_heart_mask = getLungTracheaMasks(procImg,
fg_mask,
fg_threshold,
showOutput=0)
print('...computing lung mask')
spine_mask, heart_mask = chullSpineMask(im, int_heart_mask, showOutput=0)
print('...computing spine & heart masks')
segmented_heart, segmented_lungs, segmented_trachea = segmentHeartLungsTrachea(im,
heart_mask,
lung_mask,
trachea_mask,
showOutput=0)
heart_colored, lung_colored, trachea_colored, colored_masks = getColoredMasks(im,
heart_mask,
lung_mask,
trachea_mask,
showOutput=1)
slices, PatientID = readSortedSlices('sample-dataset')
for slicePath in slices:
modelPipeline(slicePath)
Datasets
Models
