diff --git a/skimage/filter/__init__.py b/skimage/filter/__init__.py
index 8a9cffaa..04c972cc 100644
--- a/skimage/filter/__init__.py
+++ b/skimage/filter/__init__.py
@@ -4,4 +4,4 @@ from .canny import canny
 from .edges import sobel, hsobel, vsobel, hprewitt, vprewitt, prewitt
 from .tv_denoise import tv_denoise
 from .rank_order import rank_order
-from .thresholding import threshold_otsu, adaptive_threshold
+from .thresholding import threshold_otsu, threshold_adaptive
diff --git a/skimage/filter/_thresholding.pyx b/skimage/filter/_thresholding.pyx
index 88badf31..57d67e9c 100644
--- a/skimage/filter/_thresholding.pyx
+++ b/skimage/filter/_thresholding.pyx
@@ -6,12 +6,8 @@ cimport cython
 
 @cython.boundscheck(False)
 @cython.wraparound(False)
-def _adaptive_threshold(
-    np.ndarray[np.double_t, ndim=2] image,
-    int block_size,
-    double offset,
-    method
-):
+def _threshold_adaptive(np.ndarray[np.double_t, ndim=2] image,
+                        int block_size, double offset, method):
     cdef int r, c
     cdef np.ndarray[np.float64_t, ndim=2] mean_image
     if method == 'gaussian':
diff --git a/skimage/filter/thresholding.py b/skimage/filter/thresholding.py
index 09e6eaea..68ba1482 100644
--- a/skimage/filter/thresholding.py
+++ b/skimage/filter/thresholding.py
@@ -1,13 +1,13 @@
 import numpy as np
 
 from skimage.exposure import histogram
-from ._thresholding import _adaptive_threshold
+from ._thresholding import _threshold_adaptive
 
 
-__all__ = ['threshold_otsu', 'adaptive_threshold']
+__all__ = ['threshold_otsu', 'threshold_adaptive']
 
 
-def adaptive_threshold(image, block_size, offset, method='gaussian'):
+def threshold_adaptive(image, block_size, offset, method='gaussian'):
     """Applies an adaptive threshold to an array.
 
     Also known as local or dynamic thresholding where the threshold value is the
@@ -40,7 +40,7 @@ def adaptive_threshold(image, block_size, offset, method='gaussian'):
     """
     # not using img_as_float because threshold parameter wouldn't work
     image = image.astype('double')
-    return _adaptive_threshold(image, block_size, offset, method)
+    return _threshold_adaptive(image, block_size, offset, method)
 
 def threshold_otsu(image, nbins=256):
     """Return threshold value based on Otsu's method.