About the data

This dataset contains knee X-ray data for both knee joint detection and knee KL grading. The Grade descriptions are as follows:

Grade 0: Healthy knee image.
Grade 1 (Doubtful): Doubtful joint narrowing with possible osteophytic lipping
Grade 2 (Minimal): Definite presence of osteophytes and possible joint space narrowing
Grade 3 (Moderate): Multiple osteophytes, definite joint space narrowing, with mild sclerosis.
Grade 4 (Severe): Large osteophytes, significant joint narrowing, and severe sclerosis.

What is KL grading?

The Kellgren Lawrence grading system is a radiological classification of knee osteoarthritis. It progresses from grade 0 to grade IV and is based on x-rays.

Download Dataset

The dataset can be downloaded from the given link: https://drive.google.com/file/d/1NdDqPK4NLn2aV8ZdF5ilux1sfG6IyebC/view?usp=sharing

From the above link you will be able to download a zip file named ‘KneeXray.zip’. After you extract this zip file, you will get four files:

train - contains all the images that are to be used for training your model.
Train.csv - this csv file has contains the labels for the training images
test - contains 1900+ images. For these images you are required to make predictions whether the KL grading is 0, 1, 2, 3, or 4
Test.csv - this is the order of the predictions for each image that is to be submitted on the platform. Make sure the predictions you submit are with their image’s filename in the same order as given in this file.
sample_submission: This is a csv file that contains the sample submission for the data sprint.

Saving Prediction File & Sample Submission

You can find more details on how to save a prediction file here: https://discuss.dphi.tech/t/how-to-submit-predictions/548

Sample submission: You should submit a CSV file with a header row and the sample submission can be found below:

label

1

0

3

0

2

1

4

1

.

.

.

Etc.

Note that the header name should be ‘label’ else it will throw an evaluation error.

Notebook Submission

Steps to follow to submit your notebook:

Go to the Notebook section on this challenge page
Click on the 'Upload Notebook' button on top left corner as shown in the image below:
Make sure to make the visibility of your notebook as 'public' while uploading the notebook.
Provide Notebook Title, Summary, add some tags, go to next, chose a file and click on Upload.

Acknowledgement

Chen, Pingjun (2018), “Knee Osteoarthritis Severity Grading Dataset”, Mendeley Data, V1, doi: 10.17632/56rmx5bjcr.1

Data Sprint #35: Osteoarthritis Knee X-ray

Challenge Starts

Registration Ends

Challenge Ends