new - camera noise

bioMONAI/_modidx.py

@@ -94,7 +94,8 @@
                                'bioMONAI.nets.get_padding': ('nets.html#get_padding', 'bioMONAI/nets.py'),
                                'bioMONAI.nets.interpolate': ('nets.html#interpolate', 'bioMONAI/nets.py')},
             'bioMONAI.template': {'bioMONAI.template.foo': ('template.html#foo', 'bioMONAI/template.py')},
-            'bioMONAI.transforms': { 'bioMONAI.transforms.RandCrop2D': ('transforms.html#randcrop2d', 'bioMONAI/transforms.py'),
+            'bioMONAI.transforms': { 'bioMONAI.transforms.RandCameraNoise': ('transforms.html#randcameranoise', 'bioMONAI/transforms.py'),
+                                     'bioMONAI.transforms.RandCrop2D': ('transforms.html#randcrop2d', 'bioMONAI/transforms.py'),
                                      'bioMONAI.transforms.RandCrop2D.__init__': ( 'transforms.html#randcrop2d.__init__',
                                                                                   'bioMONAI/transforms.py'),
                                      'bioMONAI.transforms.RandCrop2D.before_call': ( 'transforms.html#randcrop2d.before_call',
@@ -128,6 +129,13 @@
                                                                                     'bioMONAI/transforms.py'),
                                      'bioMONAI.transforms.RandRot90.encodes': ( 'transforms.html#randrot90.encodes',
                                                                                 'bioMONAI/transforms.py'),
+                                     'bioMONAI.transforms.Resample': ('transforms.html#resample', 'bioMONAI/transforms.py'),
+                                     'bioMONAI.transforms.Resample.__init__': ( 'transforms.html#resample.__init__',
+                                                                                'bioMONAI/transforms.py'),
+                                     'bioMONAI.transforms.ScaleIntensityPercentiles': ( 'transforms.html#scaleintensitypercentiles',
+                                                                                        'bioMONAI/transforms.py'),
+                                     'bioMONAI.transforms.ScaleIntensityRange': ( 'transforms.html#scaleintensityrange',
+                                                                                  'bioMONAI/transforms.py'),
                                      'bioMONAI.transforms._get_sz': ('transforms.html#_get_sz', 'bioMONAI/transforms.py'),
                                      'bioMONAI.transforms._process_sz': ('transforms.html#_process_sz', 'bioMONAI/transforms.py')},
             'bioMONAI.visualize': { 'bioMONAI.visualize._fig_bounds': ('visualize.html#_fig_bounds', 'bioMONAI/visualize.py'),

bioMONAI/transforms.py

@@ -1,15 +1,117 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/05_transforms.ipynb.
 
 # %% auto 0
-__all__ = ['RandCrop2D', 'RandCropND', 'RandCropND_T', 'RandFlip', 'RandRot90']
+__all__ = ['Resample', 'RandCameraNoise', 'ScaleIntensityRange', 'ScaleIntensityPercentiles', 'RandCrop2D', 'RandCropND',
+           'RandCropND_T', 'RandFlip', 'RandRot90']
 
 # %% ../nbs/05_transforms.ipynb 3
 from fastai.vision.all import *
 from fastai.data.all import *
 from monai.transforms import SpatialCrop, Flip, Rotate90, Spacing
 from numpy import percentile, isscalar, float32 as np_float32
 
-# %% ../nbs/05_transforms.ipynb 13
+# %% ../nbs/05_transforms.ipynb 5
+class Resample(Spacing):
+    """
+    A subclass of Spacing that handles image resampling based on specified sampling factors or voxel dimensions.
+    
+    The `Resample` class inherits from `Spacing` and provides a flexible way to adjust the spacing (voxel size) of images by specifying either a sampling factor or explicitly providing new voxel dimensions.
+    
+    Args:
+        sampling (int, optional): Sampling factor for isotropic resampling. Default is 1, indicating no change in resolution.
+        **kwargs: Additional keyword arguments that can include 'pixdim' to specify custom voxel dimensions.
+        
+    Attributes:
+        pixdim (list or tuple): The voxel dimensions of the image after resampling. If not provided during initialization, this will be determined based on the sampling factor and original image properties.
+    
+    Methods:
+        None
+    
+    Example Usage:
+        # Creating a Resample object with a specified sampling factor
+        resampler = Resample(sampling=2)
+        
+        # Creating a Resample object with custom voxel dimensions
+        resampler = Resample(**kwargs={'pixdim': [1.5, 1.5, 3]})
+    """
+
+    def __init__(self, sampling, **kwargs):
+        """
+        Initializes the Resample class instance.
+        
+        Args:
+            sampling (int, optional): Sampling factor for isotropic resampling. Default is 1.
+            **kwargs: Additional keyword arguments that can include 'pixdim' to specify custom voxel dimensions.
+            
+        If 'pixdim' is provided in kwargs, it will be used directly; otherwise, the sampling factor will determine the new voxel dimensions.
+        
+        The Spacing class from which Resample inherits is initialized with either the provided pixdim or calculated based on the sampling factor and original image properties.
+        """
+        if 'pixdim' in kwargs:
+            super().__init__(**kwargs)
+        else:
+            super().__init__(sampling, **kwargs)
+
+
+# %% ../nbs/05_transforms.ipynb 8
+def RandCameraNoise(input_image, qe=0.7, gain=2, exp_time=0.1,
+                     dark_current=0.06, readout=2.5, bitdepth=16, offset=100,
+                     seed=42, simulation = False, camera = 'cmos', gain_variance=.1, offset_variance=5):
+
+    # Random state
+    rs = np.random.RandomState(seed=seed)
+
+    # Add shot noise
+    input_photons = input_image if simulation else input_image / gain / qe
+    photons = rs.poisson(input_photons, size=input_photons.shape)
+
+    # Convert to electrons
+    electrons = qe * photons
+
+    # Add dark noise
+    dark_noise = rs.poisson(dark_current*exp_time, size=electrons.shape)
+    electrons += dark_noise
+
+    # Add readout noise
+    read_noise = rs.normal(scale=readout**2, size=electrons.shape)
+    electrons += read_noise
+
+    if camera == 'cmos':
+        gain = rs.normal(scale=gain_variance, size=electrons.shape) + gain + rs.normal(scale=gain_variance, size=electrons.shape[0])
+        fixed_pattern = rs.normal(scale=offset_variance, size=electrons.shape[0])
+        offset = rs.normal(scale=offset_variance, size=electrons.shape)+ fixed_pattern + offset
+
+    # Convert to ADU and add offset
+    max_adu = (2**bitdepth - 1)
+    adu = (electrons * gain)
+    adu += offset
+    adu[adu > max_adu] = max_adu # pixel saturation
+
+    # pixel_type = np.uint8 if bitdepth <= 8 else np.uint16
+    # adu = adu.astype(pixel_type) # Convert to discrete numbers
+
+    return adu
+
+# %% ../nbs/05_transforms.ipynb 11
+def ScaleIntensityRange(x, mi, ma, eps=1e-20, dtype=np_float32):
+    if dtype is not None:
+        x = x.astype(dtype, copy=False)
+        mi = dtype(mi) if isscalar(mi) else mi.astype(dtype, copy=False)
+        ma = dtype(ma) if isscalar(ma) else ma.astype(dtype, copy=False)
+        eps = dtype(eps)
+        x = (x - mi) / (ma - mi + eps)
+    return x
+
+# %% ../nbs/05_transforms.ipynb 12
+def ScaleIntensityPercentiles(x, pmin=3, pmax=99.8, axis=None, eps=1e-20, dtype=np_float32):
+    """Percentile-based image normalization."""
+
+    mi = percentile(x, pmin, axis=axis, keepdims=True)
+    ma = percentile(x, pmax, axis=axis, keepdims=True)
+    return ScaleIntensityRange(x, mi, ma, eps=eps, dtype=dtype)
+
+
+# %% ../nbs/05_transforms.ipynb 16
 def _process_sz(size, ndim=3):
     if isinstance(size,int): 
         size=(size,)*ndim
@@ -20,7 +122,7 @@ def _get_sz(x):
     if not isinstance(x, Tensor): return fastuple(x.size)
     return fastuple(getattr(x, 'img_size', getattr(x, 'sz', (x.shape[1:])))) # maybe it should swap x and y axes 
 
-# %% ../nbs/05_transforms.ipynb 16
+# %% ../nbs/05_transforms.ipynb 19
 class RandCrop2D(RandTransform):
     "Randomly crop an image to `size`"
     split_idx,order = None,1
@@ -50,7 +152,7 @@ def before_call(self,
     def encodes(self, x):
         return SpatialCrop(roi_center=self.ctr, roi_size=self.size, lazy=self.lazy)(x)
 
-# %% ../nbs/05_transforms.ipynb 17
+# %% ../nbs/05_transforms.ipynb 20
 class RandCropND(RandTransform):
     """
     Randomly crops an ND image to a specified size.
@@ -103,7 +205,7 @@ def encodes(self, x):
         return SpatialCrop(roi_start=self.tl, roi_end=self.br, lazy=self.lazy)(x)
 
 
-# %% ../nbs/05_transforms.ipynb 19
+# %% ../nbs/05_transforms.ipynb 22
 class RandCropND_T(RandTransform):
     """
     Randomly crops an ND image to a specified size.
@@ -166,7 +268,7 @@ def encodes(self, x):
         return cropped_img
 
 
-# %% ../nbs/05_transforms.ipynb 21
+# %% ../nbs/05_transforms.ipynb 24
 class RandFlip(RandTransform):
     """
     Randomly flips an ND image over a specified axis.
@@ -199,7 +301,7 @@ def encodes(self, x):
         else:
             return x
 
-# %% ../nbs/05_transforms.ipynb 23
+# %% ../nbs/05_transforms.ipynb 26
 class RandRot90(RandTransform):
     """
     Randomly rotate an ND image by 90 degrees in the plane specified by axes.

nbs/00_core.ipynb

@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -20,7 +20,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -37,7 +37,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -56,7 +56,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -68,7 +68,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -86,7 +86,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -100,7 +100,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -111,7 +111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -129,7 +129,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -143,18 +143,6 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.5"
   }
  },
  "nbformat": 4,

nbs/01_data.ipynb

@@ -732,10 +732,6 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "name": "python",
-   "version": "3.11.5"
   }
  },
  "nbformat": 4,

nbs/02_io.ipynb

@@ -630,10 +630,6 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "name": "python",
-   "version": "3.11.5"
   }
  },
  "nbformat": 4,

nbs/03_losses.ipynb

@@ -397,10 +397,6 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "name": "python",
-   "version": "3.11.5"
   }
  },
  "nbformat": 4,

nbs/04_nets.ipynb

@@ -954,10 +954,6 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "name": "python",
-   "version": "3.11.5"
   }
  },
  "nbformat": 4,

nbs/06_metrics.ipynb

@@ -304,10 +304,6 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "name": "python",
-   "version": "3.11.5"
   }
  },
  "nbformat": 4,

nbs/08_datasets.ipynb

@@ -378,10 +378,6 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "name": "python",
-   "version": "3.11.5"
   }
  },
  "nbformat": 4,

nbs/09_visualize.ipynb

@@ -2408051,10 +2408051,6 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "name": "python",
-   "version": "3.11.5"
   }
  },
  "nbformat": 4,

nbs/901_demo_RI2FL_2d.ipynb

@@ -909,10 +909,6 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "name": "python",
-   "version": "3.11.5"
   }
  },
  "nbformat": 4,

nbs/index.ipynb

@@ -198,10 +198,6 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "name": "python",
-   "version": "3.11.5"
   }
  },
  "nbformat": 4,