Department of Biomedical Informatics (BMI), Emory University School of Medicine

Mentors: Student: Nishchal Singi

<p>This project aims to develop a potential frontend for Niffler. Niffler is currently a command-line tool where the user has to download it in their system and run python commands to retrieve the DICOM images. The main aim of Niffler is to retrieve DICOM images from multiple PACS and store them as png images or metadata files. This can be done currently via the command line. Enhancing this with a frontend and making this a web application would be beneficial and easy to use by a large number of non-technical users and clients.</p>

Mentors: Student: Aryan Verma

<p>Development of an AI-based Android Application for distinguishing COVID-19 and Pneumonia using Computed Tomography Images.The project aims at development of an Android application capable of efficiently generating a report based on AI capabilities of the well trained neural network, using the Computed Tomography (CT) Images of patients as a part of the project. The report will show the AI predicted results for distinguishing covid-19 and non-Covid-19 disease using the CT Images. These results will also contain saliency maps and segmented regions to better outline and detect the affected regions from CT Images. The application would be equipped with computer vision algorithms such as contrast stretching, adaptive and global thresholding, Image enhancement and many state of the art methods to carefully present every detail from the CT image. The backend of the application would be optimal for performance of trained Deep Learning Models and computer Vision Algorithms.</p>

Mentors: Student: Viraj Patel

<p>Tensorflow GUI will help everyone from beginners to professionals in their day to day work. People who are new to the field of deep learning can use this to build , train and test neural networks without requiring in depth programming knowledge or tensorflow framework. Professionals can use it to create boilerplate code , train and test their models.</p>

Mentors: Student: Chinmay Vibhute

<p>This Project aims to develop unit and integration tests for the Niffler modules and implement automated testing using Continuous Integration. The Testing framework will include both manual testing as well as automated testing to reduce overall manual effort in testing. The project will introduce checks to confirm that the commits to the codebase do not break the functionality of Niffler, before each major production release. These tests will significantly reduce the potential for bugs in the codebase, allowing the deployment of newer versions seamlessly.</p>

Mentors: Student: Özgür Kara

<p>The project is aiming to develop a GUI for the simulations of reinforcement learning so that users, particularly, the researchers can be able to test and implement their ideas and algorithms about reinforcement learning with the embedded environments easily even though they are not able to implement the codes in a fast way. The GUI will involve an interface that is encompassing graphical blocks which should be clickable by the user. Users will be able to create an execution flow by selecting the graphical blocks which are referring to the selection of the environment (e.g. CartPole-v1, Acrobot-v1, etc.) and the algorithms. Furthermore, the relevant information such as Q-values, reward functions will be shown on the GUI at any time during training and testing.</p>