diff --git a/skimage/transform/radon_transform.py b/skimage/transform/radon_transform.py
index 6009c54a..1ebd26c6 100644
--- a/skimage/transform/radon_transform.py
+++ b/skimage/transform/radon_transform.py
@@ -136,7 +136,7 @@ def iradon(radon_image, theta=None, output_size=None,
         Number of rows and columns in the reconstruction.
     filter : str, optional (default ramp)
         Filter used in frequency domain filtering. Ramp filter used by default.
-        Filters available: ramp, shepp-logan, cosine, hamming, hann
+        Filters available: ramp, shepp-logan, cosine, hamming, hann.
         Assign None to use no filter.
     interpolation : str, optional (default 'linear')
         Interpolation method used in reconstruction. Methods available:
@@ -267,13 +267,14 @@ def order_angles_golden_ratio(theta):
     The method used here is that of the golden ratio introduced
     by T. Kohler.
 
-    References:
-        -Kohler, T. "A projection access scheme for iterative
-        reconstruction based on the golden section." Nuclear Science
-        Symposium Conference Record, 2004 IEEE. Vol. 6. IEEE, 2004.
-        -Winkelmann, Stefanie, et al. "An optimal radial profile order
-        based on the Golden Ratio for time-resolved MRI."
-        Medical Imaging, IEEE Transactions on 26.1 (2007): 68-76.
+    References
+    ----------
+    .. [1] Kohler, T. "A projection access scheme for iterative
+           reconstruction based on the golden section." Nuclear Science
+           Symposium Conference Record, 2004 IEEE. Vol. 6. IEEE, 2004.
+    .. [2] Winkelmann, Stefanie, et al. "An optimal radial profile order
+           based on the Golden Ratio for time-resolved MRI."
+           Medical Imaging, IEEE Transactions on 26.1 (2007): 68-76.
     """
     interval = 180
 
@@ -336,7 +337,7 @@ def iradon_sart(radon_image, theta=None, image=None, projection_shifts=None,
     Returns
     -------
     output : ndarray
-      Reconstructed image.
+        Reconstructed image.
 
     Notes
     -----
@@ -353,20 +354,21 @@ def iradon_sart(radon_image, theta=None, image=None, projection_shifts=None,
     reconstruction. Further iterations will tend to enhance high-frequency
     information, but will also often increase the noise.
 
-    References:
-        -AC Kak, M Slaney, "Principles of Computerized Tomographic
-        Imaging", IEEE Press 1988.
-        -AH Andersen, AC Kak, "Simultaneous algebraic reconstruction technique
-        (SART): a superior implementation of the ART algorithm", Ultrasonic
-        Imaging 6 pp 81--94 (1984)
-        -S Kaczmarz, "Angenäherte auflösung von systemen linearer
-        gleichungen", Bulletin International de l’Academie Polonaise des
-        Sciences et des Lettres 35 pp 355--357 (1937)
-        -Kohler, T. "A projection access scheme for iterative
-        reconstruction based on the golden section." Nuclear Science
-        Symposium Conference Record, 2004 IEEE. Vol. 6. IEEE, 2004.
-        -Kaczmarz' method, Wikipedia,
-        http://en.wikipedia.org/wiki/Kaczmarz_method
+    References
+    ----------
+    .. [1] AC Kak, M Slaney, "Principles of Computerized Tomographic
+           Imaging", IEEE Press 1988.
+    .. [2] AH Andersen, AC Kak, "Simultaneous algebraic reconstruction technique
+           (SART): a superior implementation of the ART algorithm", Ultrasonic
+           Imaging 6 pp 81--94 (1984)
+    .. [3] S Kaczmarz, "Angenäherte auflösung von systemen linearer
+           gleichungen", Bulletin International de l’Academie Polonaise des
+           Sciences et des Lettres 35 pp 355--357 (1937)
+    .. [4] Kohler, T. "A projection access scheme for iterative
+           reconstruction based on the golden section." Nuclear Science
+           Symposium Conference Record, 2004 IEEE. Vol. 6. IEEE, 2004.
+    .. [5] Kaczmarz' method, Wikipedia,
+           http://en.wikipedia.org/wiki/Kaczmarz_method
     """
     if radon_image.ndim != 2:
         raise ValueError('radon_image must be two dimensional')