115 lines
2.7 KiB
Python
115 lines
2.7 KiB
Python
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import os
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import statistics
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import imageio
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from PIL import Image, ImageFilter, ImageMath
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import numpy as np
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import SimpleITK as sitk
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STUDY_PATH = "/media/nfs/SRS/storage/0/CT Without Contrast-Brain_55121720"
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STUDY_PATH = '/media/nfs/SRS/storage/0/MRI With_Without Contrast--Brain_54141890'
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MODEL_PATH = '/home/xfr/nni/model-5-64/TwNuKtj7/best_zdoyO.pth'
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# Write image series using SimpleITK
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def flush_file(shape, fileNames):
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if len(fileNames) > 1:
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xy = min(shape)
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outfile = '%s.nii.gz' % os.path.basename(fileNames[0]).split('.')[0]
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img = sitk.ReadImage(fileNames)
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img.SetSpacing([1.0,1.0, 1.0*xy/len(fileNames)])
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sitk.WriteImage(img, outfile)
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COR_ABS_THRESHOLD = 0.5
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COR_REL_THRESHOLD = 0.8
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def lower_bound(cors, begin, end):
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# THRESHOLD = 3
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THRESHOLD = 5
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return np.mean(cors[begin+1:end]) - np.std(cors[begin+1:end]) * THRESHOLD
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def lower_bound(cors, begin, end):
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# Not so good
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# THRESHOLD = 1.5
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THRESHOLD = 2
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Q1 = np.percentile(cors[begin+1:end], 25, interpolation = 'lower')
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Q3 = np.percentile(cors[begin+1:end], 75, interpolation = 'higher')
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IQR = Q3 - Q1
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return Q1 - THRESHOLD * IQR
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NewSer = None
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def check_low(cors, begin, end):
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if end - begin < 2:
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return
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mini = np.min(cors[begin+1:end])
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if mini > COR_ABS_THRESHOLD and mini > lower_bound(cors, begin, end):
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# exit()
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return
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argmin = np.argmin(cors[begin+1:end]) + begin+1
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print(begin, end, lower_bound(cors, begin, end), mini, argmin)
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NewSer[argmin] = 1
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check_low(cors, begin, argmin)
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check_low(cors, argmin, end)
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# exit()
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def main():
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global NewSer
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old_shape = None
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old_array = None
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old_cor = COR_ABS_THRESHOLD
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fileNames = []
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shapes = []
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cors = []
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for jpg_file in sorted(os.listdir(STUDY_PATH)):
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jpg_path = os.path.join(STUDY_PATH, jpg_file)
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array = np.asarray(Image.open(jpg_path).convert('L'))
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shape = array.shape
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# LB = lower_bound(cors)
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if not fileNames:
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cor = 0
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else:
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if old_shape != shape:
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cor =0
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else:
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cor = np.corrcoef(old_array.flat, array.flat)[0,1]
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fileNames.append(jpg_path)
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shapes.append(shape)
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cors.append(cor)
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old_array = array
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old_shape = shape
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old_cor = cor
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length = len(fileNames)
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# print(length)
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# exit()
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for i in range(length):
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# print(i)
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print(fileNames[i], i, shapes[i], cors[i])
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NewSer = np.zeros(length)
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check_low(cors, 0, length)
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for i in range(length):
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# print(i)
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print(fileNames[i], i, shapes[i], cors[i], '***' if NewSer[i] else '')
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if __name__ == '__main__':
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main()
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