diff --git a/src/ggrappa/application.py b/src/ggrappa/application.py
index 0e901cd..3eda1de 100644
--- a/src/ggrappa/application.py
+++ b/src/ggrappa/application.py
@@ -77,15 +77,15 @@ def apply_grappa_kernel(sig,
             shift_y, shift_z = shifts
     else:
         shift_y, shift_z = abs(sig).sum(0).sum(-1).nonzero()[0]
-        #sig = torch.nn.functional.pad(sig,  (xpos, (sblx-xpos-tblx),
-        #                                    (af[1] - zpos)%tblz + zpos, (sblz-zpos-tblz),
-        #                                    (af[0] - ypos)%tbly + ypos, (sbly-ypos-tbly)))
+        sig = torch.nn.functional.pad(sig,  (xpos, (sblx-xpos-tblx),
+                                           (af[1] - zpos)%tblz + zpos, (sblz-zpos-tblz),
+                                           (af[0] - ypos)%tbly + ypos, (sbly-ypos-tbly)))
 
     rec = torch.zeros_like(sig)
 
     size_chunk_y = sbly + tbly*(batch_size - 1)
-    y_ival = range(shift_y, max(rec.shape[1] - sbly, 1), tbly*batch_size)
-    z_ival = np.arange(0, max(rec.shape[2] - sblz, 1), tblz)
+    y_ival = range(shift_y, max(rec.shape[1] - sbly - 1, 1), tbly*batch_size)
+    z_ival = np.arange(0, max(rec.shape[2] - sblz - 1, 1), tblz)
     
     if not quiet:
         logger.info("GRAPPA Reconstruction...")
@@ -95,7 +95,7 @@ def apply_grappa_kernel(sig,
     for y in tqdm(y_ival, disable=quiet):
         sig_y = sig[:,y:y+size_chunk_y]
         sig_y = sig_y.cuda() if cuda and cuda_mode in ["all", "application"] else sig_y
-        zival = cnt + z_ival
+        zival = z_ival[z_ival >= cnt.numpy()]
         for z in zival:
             blocks = sig_y[:,:, z:z+sblz, :].unfold(dimension=1, size=sbly, step=tbly).unfold(dimension=3, size=sblx, step=tblx)
             blocks = blocks.permute(1,3,0,4,2,5)