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Updated the Sunnybrook dataset link in the medical imaging example #2075

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Updated the Sunnybrook dataset link in the medical imaging example #2075

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2 changes: 1 addition & 1 deletion examples/medical-imaging/README.md
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Expand Up @@ -22,7 +22,7 @@ We will train an image segmentation neural network and learn how to implement a
We will also see how transfer learning can help in cases where the dataset is too small to reach the desired accuracy.
Lastly, we will see how a finer segmentation model helps address the issue of coarse segmentation contours.

We will use the [Sunnybrook Left Ventricle Segmentation Challenge Dataset](http://smial.sri.utoronto.ca/LV_Challenge/) to train a neural network to segment the Left Ventricle out of MRI images.
We will use the [Sunnybrook Left Ventricle Segmentation Challenge Dataset](http://www.cardiacatlas.org/studies/sunnybrook-cardiac-data/) to train a neural network to segment the Left Ventricle out of MRI images.
The dataset was originally published in:

> Radau P, Lu Y, Connelly K, Paul G, Dick AJ, Wright GA. “Evaluation Framework for Algorithms Segmenting Short Axis Cardiac MRI.” The MIDAS Journal – Cardiac MR Left Ventricle Segmentation Challenge, http://hdl.handle.net/10380/3070
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