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kneehit / Bone-Age

Building multi-input CNN for predicting the age of bones from X-Ray and gender using PyTorch.
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age-detection bone cnn hybrid-neural-network xray

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Bone Age Predictor

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Description

The aim of this project is to predict Bone Age (in months) from the X-Ray and Gender.
Dataset - https://www.kaggle.com/kmader/rsna-bone-age

Motivation

I chose this project primarily since it combines more than one form of data and simply using pretrained model won't work in this scenario.

Following are the challenges I encountered (and overcame) in this project:

  1. Image data as well as categorical data is provided and hence will require a custom model.
  2. Unlike most image recognition problem, the target variable is continuous and the input image has only single channel.
  3. Since the ouput is continuous, the network can predict negative values (whereas age can only be positive).

Results

Predictions (in number of months) on the test dataset can be seen below

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Closing Thoughts

Although the predictions are decent, there is certainly room for improvement. Following things can be experimented:

  1. Changing the architecture
    a. Adding more layers - convolutional/FC/ResNet blocks
    b. Replacing ResNet layers by layers of other CNN architecture like Inception, ResNeXt, etc.
  2. Using features from convolutional layers of a CNN which is pretrained on X-Rays of hands.