GSoC Week 10

There was a lot of struggle this week and I am also expecting a lot of difficulties to come by the further weeks.

The two biggest challenges I am facing,

- Integration of the RSNA Kaggle Mammography classification model

- React hook implementation in the OHIF viewer

RSNA Kaggle Mammography Model

The code base and model complexity that are put available by the top Kaggle solutions of the RSNA Kaggle competitions are large and takes time to decode. I've been working on the top solution that uses a YOLOX model to crop the image and then a CONVNEXT model to perform the classification. The code that's provided is for training and evaluation. It needs to be converted to perform a single image inference. The code base is optimized for specific GPUs but for our case it needs to be generalized to run on CPU or GPU (any).

I was able to run the models but the YOLOX model is throwing smaller boxes to crop off. I need to debug and check what is missing. If it's still the case I will need to check other top Kaggle solutions.

React hook implementation in the OHIF viewer

Last time I had to work on Java and Spring Boot to implement functionalities for the model selection module. A new requirement is to implement a hook in the React OHIF module that would enable a user to click on a button and trigger the specific AI Model. I will need to work on implementing that in React. Since I am new React I will need to start picking it up and explore the code. Post this I will need to modify or add Java code in the controller part that will trigger the AI Model Service.

I will need to prepare and work on these tasks and aim to finish GSoC 2023 successfully.

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