9393
9494 import torchio as tio
9595 subject = tio.datasets.Colin27()
96- subject.plot()
96+ subject.plot(figsize=(9, 9) )
9797
9898
9999:class: `Pediatric `
104104
105105 import torchio as tio
106106 subject = tio.datasets.Pediatric((4.5, 8.5))
107- subject.plot()
107+ subject.plot(figsize=(14, 9) )
108108
109109
110110:class: `Sheep `
@@ -140,7 +140,7 @@ ITK-SNAP
140140.. plot ::
141141
142142 import torchio as tio
143- tio.datasets.BrainTumor().plot()
143+ tio.datasets.BrainTumor().plot(figsize=(16, 9) )
144144
145145
146146:class: `T1T2 `
@@ -162,7 +162,7 @@ ITK-SNAP
162162
163163 import torchio as tio
164164 subject = tio.datasets.AorticValve()
165- subject.plot()
165+ subject.plot(figsize=(12, 9) )
166166
167167
1681683D Slicer
198198
199199 import torchio as tio
200200 subject = tio.datasets.FPG(load_all=True)
201- subject.plot()
201+ subject.plot(figsize=(16, 9) )
202202
203203
204204MedMNIST
@@ -313,3 +313,17 @@ MedMNIST
313313 tensor = rearrange(tensor, pattern, b1=rows, b2=cols)
314314 sx = tensor.shape[1]
315315 plt.imshow(tensor[0, sx // 2], cmap='gray')
316+
317+ ZonePlate
318+ ---------
319+
320+ .. currentmodule :: torchio.datasets.zone_plate
321+
322+
323+ .. autoclass :: ZonePlate
324+
325+ .. plot ::
326+
327+ from torchio.datasets import ZonePlate
328+ zone_plate = ZonePlate(size=201)
329+ zone_plate.plot(interpolation='bicubic')
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