diff --git a/src/cdtools/datasets/ptycho_2d_dataset.py b/src/cdtools/datasets/ptycho_2d_dataset.py
index bdf4e60..8b6f6d8 100644
--- a/src/cdtools/datasets/ptycho_2d_dataset.py
+++ b/src/cdtools/datasets/ptycho_2d_dataset.py
@@ -400,9 +400,40 @@ class Ptycho2DDataset(CDataset):
                 divisor_override=1)[0,0]
 
 
+    def remove_translations_mask(self, mask_remove):
+        """Removes one or more translation positions, and their associated
+        properties, from the dataset using logical indexing.
+
+        This takes a 1D mask (boolean torch tensor) with the length
+        self.translations.shape[0] (i.e., the number of individual
+        translated points). Patterns, translations, and intensities
+        associated with indices that are "True" will be removed.
+
+        Parameters:
+        ----------
+        mask_remove : 1D torch.tensor(dtype=torch.bool)
+            The boolean mask indicating which elements are to be removed from
+            the dataset. True indicates that the corresponding element will be
+            removed.
+        """
+
+        # Check that the mask is the right size
+        if mask_remove.shape != t.Size([self.translations.shape[0]]):
+            raise ValueError(
+                'The mask must have the same length as the number of translations in the dataset.'
+            )
+
+        # Update patterns, translations, and intensities
+        self.patterns = self.patterns[~mask_remove]
+        self.translations = self.translations[~mask_remove]
+
+        if hasattr(self, 'intensities') and self.intensities is not None:
+            self.intensities = self.intensities[~mask_remove]
+
+
     def crop_translations(self, roi):
         """Shrinks the range of translation positions that are analyzed
-        
+
         This deletes all diffraction patterns associated with x- and 
         y-translations that lie outside of a specified rectangular
         region of interest. In essence, this operation crops the "relative 
@@ -420,7 +451,7 @@ class Ptycho2DDataset(CDataset):
             do not matter as long as roi[:2] and roi[2:] correspond with 
             the x and y coordinates, respectively.
         """
-        
+
         # Pull out the bounds of the ROI, ensuring that left < right and 
         #   top < bottom
         x_left, x_right = sorted(roi[:2])
@@ -441,9 +472,5 @@ class Ptycho2DDataset(CDataset):
                              '(i.e., patterns and translations will be empty).'
                              ' Please redefine the bounds of the roi.')
 
-        # Update patterns and translations
-        self.patterns = self.patterns[inside_roi]
-        self.translations = self.translations[inside_roi]
-        
-        if hasattr(self, 'intensities') and self.intensities is not None:
-            self.intensities = self.intensities[inside_roi]
\ No newline at end of file
+        # Remove translations outside the ROI
+        self.remove_translations_mask(~inside_roi)
diff --git a/tests/test_datasets.py b/tests/test_datasets.py
index 9e72fb7..6897991 100644
--- a/tests/test_datasets.py
+++ b/tests/test_datasets.py
@@ -1,4 +1,4 @@
-from cdtools.datasets import *
+from cdtools.datasets import CDataset, Ptycho2DDataset
 from cdtools.tools import data as cdtdata
 import numpy as np
 import torch as t
@@ -340,7 +340,31 @@ def test_Ptycho2DDataset_downsample(test_ptycho_cxis):
             if dataset.background is not None:
                 assert np.allclose(np.array(dataset.background.shape) // factor,
                                    np.array(copied_dataset.background.shape))
-        
+
+
+def test_Ptycho2DDataset_remove_translations_mask(ptycho_cxi_1):
+    # Grab dataset
+    cxi, expected = ptycho_cxi_1
+    dataset = Ptycho2DDataset.from_cxi(cxi)
+    copied_dataset = deepcopy(dataset)
+
+    # Test 1: Complain when the the mask is not the same shape as the pattern
+    # length
+    with pytest.raises(ValueError) as excinfo:
+        copied_dataset.remove_translations_mask(mask_remove=t.zeros(10))
+    assert ('The mask must have the same length') in str(excinfo.value)
+
+    # Test 2: Remove the mask from the dataset
+    mask_success = t.zeros(len(copied_dataset.patterns))
+    mask_success[1] = 1
+    mask_success[10] = 1
+    mask_success[-1] = 1
+    mask_success = mask_success.bool()
+    copied_dataset.remove_translations_mask(mask_remove=mask_success)
+
+    # test if the mask is removed and patterns length is correct
+    assert len(copied_dataset.patterns) == len(mask_success) - 3
+
 
 def test_Ptycho2DDataset_crop_translations(ptycho_cxi_1):
     # Grab dataset