diff --git a/skimage/transform/tests/test_radon_transform.py b/skimage/transform/tests/test_radon_transform.py
index e5df9b8d..ae25c970 100644
--- a/skimage/transform/tests/test_radon_transform.py
+++ b/skimage/transform/tests/test_radon_transform.py
@@ -320,54 +320,57 @@ def test_iradon_sart():
 
     shepp_logan = imread(os.path.join(data_dir, "phantom.png"), as_grey=True)
     image = rescale(shepp_logan, scale=0.4)
-    theta = np.linspace(0., 180., image.shape[0], endpoint=False)
-    sinogram = radon(image, theta, circle=True)
-    reconstructed = iradon_sart(sinogram, theta)
+    theta_ordered = np.linspace(0., 180., image.shape[0], endpoint=False)
+    theta_missing_wedge = np.linspace(0., 150., image.shape[0], endpoint=True)
+    for theta, error_factor in ((theta_ordered, 1.),
+                                (theta_missing_wedge, 2.)):
+        sinogram = radon(image, theta, circle=True)
+        reconstructed = iradon_sart(sinogram, theta)
 
-    if debug:
-        from matplotlib import pyplot as plt
-        plt.figure()
-        plt.subplot(221)
-        plt.imshow(image, interpolation='nearest')
-        plt.subplot(222)
-        plt.imshow(sinogram, interpolation='nearest')
-        plt.subplot(223)
-        plt.imshow(reconstructed, interpolation='nearest')
-        plt.subplot(224)
-        plt.imshow(reconstructed - image, interpolation='nearest')
-        plt.show()
+        if debug:
+            from matplotlib import pyplot as plt
+            plt.figure()
+            plt.subplot(221)
+            plt.imshow(image, interpolation='nearest')
+            plt.subplot(222)
+            plt.imshow(sinogram, interpolation='nearest')
+            plt.subplot(223)
+            plt.imshow(reconstructed, interpolation='nearest')
+            plt.subplot(224)
+            plt.imshow(reconstructed - image, interpolation='nearest')
+            plt.show()
 
-    delta = np.mean(np.abs(reconstructed - image))
-    print('delta (1 iteration) =', delta)
-    assert delta < 0.025
-    reconstructed = iradon_sart(sinogram, theta, reconstructed)
-    delta = np.mean(np.abs(reconstructed - image))
-    print('delta (2 iterations) =', delta)
-    assert delta < 0.015
+        delta = np.mean(np.abs(reconstructed - image))
+        print('delta (1 iteration) =', delta)
+        assert delta < 0.016 * error_factor
+        reconstructed = iradon_sart(sinogram, theta, reconstructed)
+        delta = np.mean(np.abs(reconstructed - image))
+        print('delta (2 iterations) =', delta)
+        assert delta < 0.013 * error_factor
 
-    np.random.seed(1239867)
-    shifts = np.random.uniform(-3, 3, sinogram.shape[1])
-    x = np.arange(sinogram.shape[0])
-    sinogram_shifted = np.vstack(np.interp(x + shifts[i], x, sinogram[:, i])
-                                 for i in range(sinogram.shape[1])).T
-    reconstructed = iradon_sart(sinogram_shifted, theta,
-                                projection_shifts=shifts)
-    if debug:
-        from matplotlib import pyplot as plt
-        plt.figure()
-        plt.subplot(221)
-        plt.imshow(image, interpolation='nearest')
-        plt.subplot(222)
-        plt.imshow(sinogram_shifted, interpolation='nearest')
-        plt.subplot(223)
-        plt.imshow(reconstructed, interpolation='nearest')
-        plt.subplot(224)
-        plt.imshow(reconstructed - image, interpolation='nearest')
-        plt.show()
+        np.random.seed(1239867)
+        shifts = np.random.uniform(-3, 3, sinogram.shape[1])
+        x = np.arange(sinogram.shape[0])
+        sinogram_shifted = np.vstack(np.interp(x + shifts[i], x, sinogram[:, i])
+                                    for i in range(sinogram.shape[1])).T
+        reconstructed = iradon_sart(sinogram_shifted, theta,
+                                    projection_shifts=shifts)
+        if debug:
+            from matplotlib import pyplot as plt
+            plt.figure()
+            plt.subplot(221)
+            plt.imshow(image, interpolation='nearest')
+            plt.subplot(222)
+            plt.imshow(sinogram_shifted, interpolation='nearest')
+            plt.subplot(223)
+            plt.imshow(reconstructed, interpolation='nearest')
+            plt.subplot(224)
+            plt.imshow(reconstructed - image, interpolation='nearest')
+            plt.show()
 
-    delta = np.mean(np.abs(reconstructed - image))
-    print('delta (1 iteration, shifted sinogram) =', delta)
-    assert delta < 0.025
+        delta = np.mean(np.abs(reconstructed - image))
+        print('delta (1 iteration, shifted sinogram) =', delta)
+        assert delta < 0.018 * error_factor
 
 if __name__ == "__main__":
     from numpy.testing import run_module_suite