[feature] Add RescaleIntensity & ZNormalization & ClampIntensity transforms #2241
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| def transform(self, results: dict) -> dict: | ||
| img = results['img'] | ||
| img = self.clamp(img) |
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| img = self.clamp(img) | |
| img = np.clip(img, self.t_min, self.t_max) |
| def clamp(self, img): | ||
| return np.clip(img, self.t_min, self.t_max) |
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Perhaps we can delete L1411-1412 since np.clip() could be directly used in def transform()?
| self.channel_wise = channel_wise | ||
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| def _normalize(self, img: np.ndarray, mean=None, std=None): | ||
| slices = np.ones_like(img, dtype=bool) |
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What does slices = np.ones_like(img, dtype=bool) for?
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I find that the "slices" is designed for the case that we only want to normalize the non-zero intensity of the image in MONAI. But I haven't added this function. In this version, the "slices" is not necessary. I will remove it. Thanks!
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I find that the "slices" is designed for the case that we only want to normalize the non-zero intensity of the image in MONAI. But I haven't added this function. In this version, the "slices" is not necessary. I will remove it. Thanks!
OK, got it! Thanks. Shall we add this normalize the non-zero intensity of the image function in the future? Do you think this function is important in medical image segmentation?
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From my experiences so far, the difference of using it is slight most of the time but it's meaningful.
Adding it would be a better idea. Thanks!
| mean (float, optional): the mean to subtract by | ||
| Defaults to None. | ||
| std (float, optional): the standard deviation to divide by | ||
| Defaults to None. |
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Please add docstring about channel_wise .
Codecov ReportBase: 83.55% // Head: 83.45% // Decreases project coverage by
Additional details and impacted files@@ Coverage Diff @@
## dev-1.x #2241 +/- ##
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- Coverage 83.55% 83.45% -0.10%
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Files 140 141 +1
Lines 7958 8062 +104
Branches 1191 1208 +17
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+ Hits 6649 6728 +79
- Misses 1119 1139 +20
- Partials 190 195 +5
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Hi, @kellyiss thanks for your nice PR. Please fix the unit test problem. We would review it ASAP. |
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Needed to convert `timesteps` to `float32` a bit sooner. Fixes open-mmlab#1537
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Hi @kellyiss ！We are grateful for your efforts in helping improve this open-source project during your personal time. |
Motivation
Support rescale intensity, znormalization and clamp intensity for medical data.