Add example image to README

README.md

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 `deepcell-spots` is a deep learning library for fluorescent spot detection image analysis. It allows you to apply pre-existing models and train new deep learning models for spot detection. It is written in Python and built using [TensorFlow](https://github.com/tensorflow/tensorflow), [Keras](https://www.tensorflow.org/guide/keras) and [DeepCell](https://github.com/vanvalenlab/deepcell-tf). More detailed documentation is available [here](https://deepcell-spots.readthedocs.io/).
 
+# ![Spot Detection Example](https://raw.githubusercontent.com/vanvalenlab/deepcell-spots/mly/docs/docs/images/spot_montage.png)
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 ## DeepCell Spots Application
 
 `deepcell-spots` contains an applications that greatly simplify the implementation of deep learning models for spot detection. `deepcell-spots.applications.SpotDetection` contains a pre-trained model for fluorescent spot detection on images derived from assays such as RNA FISH and in-situ sequencing. This model returns a list of coordinate locations for fluorescent spots detected in the input image. `deepcell-spots.applications.Polaris` pairs this spot detection model with [DeepCell](https://github.com/vanvalenlab/deepcell-tf) models for nuclear and cytoplasmic segmentation.