質問編集履歴
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Jupyter Lab version 1.1.4
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[こちらのtrainのなかにあります。](https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification/data)
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コードはあまりみないのでなれないと思います。ですので、簡単にまとめます。
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dicom形式のmri画像をflairモダリティをt1,t2から作成しています。
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つまり、画像が３つ重なっていて、それをresampleしてるってことです。
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shapeがあっていればいいのではないのですか？
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よくわかりかねます。そのあたりが、グレイスケールに変更しているのにも関わらずです.
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```ここに言語を入力
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reader = sitk.ImageSeriesReader()
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reader.LoadPrivateTagsOn()
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def resample(image, ref_image):
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resampler = sitk.ResampleImageFilter()
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resampler.SetReferenceImage(ref_image)
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resampler.SetInterpolator(sitk.sitkLinear)
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resampler.SetTransform(sitk.AffineTransform(image.GetDimension()))
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resampler.SetOutputSpacing(ref_image.GetSpacing())
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resampler.SetSize(ref_image.GetSize())
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resampler.SetOutputDirection(ref_image.GetDirection())
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resampler.SetOutputOrigin(ref_image.GetOrigin())
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resampler.SetDefaultPixelValue(image.GetPixelIDValue())
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resamped_image = resampler.Execute(image)
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return resamped_image
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%%time
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# filenamesDICOM = reader.GetGDCMSeriesFileNames(f'{train_path}/{train_dirs[2]}/T1w')
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filenamesDICOM = reader.GetGDCMSeriesFileNames(f'{train_path}/00524/T1w')
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reader.SetFileNames(filenamesDICOM)
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t1_sitk = reader.Execute()
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filenamesDICOM = reader.GetGDCMSeriesFileNames(f'{train_path}/00524/FLAIR')
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# filenamesDICOM = reader.GetGDCMSeriesFileNames(f'{train_path}/{train_dirs[2]}/FLAIR')
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reader.SetFileNames(filenamesDICOM)
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flair_sitk = reader.Execute()
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# filenamesDICOM = reader.GetGDCMSeriesFileNames(f'{train_path}/{train_dirs[2]}/T2w')
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filenamesDICOM = reader.GetGDCMSeriesFileNames(f'{train_path}/00524/T2w')
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reader.SetFileNames(filenamesDICOM)
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t2_sitk = reader.Execute()
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flair_resampled = resample(flair_sitk, t1_sitk)
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t2_resampled = resample(t2_sitk, t1_sitk)
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t1_sitk_array = normalize(sitk.GetArrayFromImage(t1_sitk))
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flair_resampled_array = normalize(sitk.GetArrayFromImage(flair_resampled))
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t2_resampled_array = normalize(sitk.GetArrayFromImage(t2_resampled))
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stacked = np.stack([t1_sitk_array, t2_resampled_array, flair_resampled_array,])
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to_rgb = stacked[:,t1_sitk_array.shape[0]//2,:,:].transpose(1,2,0)
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im = Image.fromarray((to_rgb * 255).astype(np.uint8))
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```
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### 該当のソースコード
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