saeedshurrab/awesome-self-supervised-learning-in-medical-imaging

This repository is mainly dedicated for listing the recent research advancements in the application of Self-Supervised-Learning in medical images computing field

📋 Intro:

Saeed Shurrab completed an MSc in Data Science and Artificial Intelligence at Jordan University of Science and Technology with the German Academic Exchange Scholarship (DAAD). He graduated in 2022 with Distinction. Prior to that, he completed a BSc in Industrial and Systems Engineering from the Islamic University of Gaza - Palestine in 2014. His keen interest in data analytics and beliefs in the role that data can play in creating robust decisions and better solutions encouraged him to join the field of data science. Currently, Saeed focuses on developing deep neural networks and their applications to healthcare problems.

🔭 I’m currently working as:

Research Assistant - Clinical AI Lab - New York University Abu Dhabi.

📫 Feel free to reach me via:

1. [email protected]
2. [email protected]
3. [email protected]

💬 Follow my latest updates on:

https://saeedshurrab.github.io/

🌱 Featured publications

1. Self-supervised learning methods and applications in medical imaging analysis: a survey
2. Attitudes Evaluation Toward COVID-19 Pandemic: An Application of Twitter Sentiment Analysis and Latent Dirichlet Allocation

💬 Connect with me:

⚡ Programming languages and packages:

🌱 My Github summary:

awesome-self-supervised-learning-in-medical-imaging's Issues

Recommendation of our recent paper.

Hello,
I came across your repo, and it seems to be a good summary of recent advance in Medical image with self-supervised learning.

Here I would like to recommend a recent paper from my group, which addresses uniquely the pretraining for decoder of a segmentation network. This work does not belong to contrastive or predictive categories and may be interesting to have more publicity.

Thanks for considering adding it into your list.

https://arxiv.org/abs/2202.02371

some words, not issue

I'm sorry if this bothers you,
When I searching the paper about medical image in arxiv, I found your paper is so fucking nice. I got a lot from the paper and help me reduce lots of time. Stared, I gonna recommend your paper to others.

Recommend our work with codes available.

Hi there,

Thanks for your great work! I'm writing to recommend our AAAI 2021 paper, Context Matters: Graph-based Self-supervised Representation Learning for Medical Images to your repo, it belongs to the contrastive category. Would you please kindly add it? Thanks!

Paper: https://ojs.aaai.org/index.php/AAAI/article/view/16620
Code: https://github.com/batmanlab/Context_Aware_SSL

Regards,
Li

Recommend our work with codes available.

Good job, bro. I would like to share our recent work [Towards better understanding and better generalization of few-shot classification in histology images with contrastive learning] (https://arxiv.org/abs/2202.09059) which has been published with ICLR2022 and codes available in https://github.com/TencentAILabHealthcare/Few-shot-WSI

I have starred this repo. Thanks for your collections.