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@Maastro-CDS-Imaging-Group @AIM-Harvard @SynthRAD2023
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surajpaib/README.md

Hello! I'm Suraj Pai
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About me

Born to a family of doctors, I was dubbed the black sheep, tinkering with computers and fascinated by anything technological. But, when you grow up in a household where medical jargon dominates conversations, a particular sentiment toward it develops. Progressing through my career, I have attempted to combine my passion for technology with my keen interest in medicine.

🔨 I'm currently working on,

  • 🔬 Building and evaluating deep learning based biomarkers to help out in the clinic at AIM Harvard

  • 🔥 Contributing and developing a simplified framework to run deep learning models project-lighter/lighter

⏮️ Previously I've enjoyed working with,

  • 🔍 Image synthesis (CBCT ▶️ CT) and segmentation (CT) techniques to improve radiotherapy at Maastro Clinic and ganslate-team

  • 🛠️ Various Computer Vision-based functionality for a revolutionary customer assistance platform at Blinkin


Education Highlights


Tools, Frameworks and Languages

I find myself most comfortable with,


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  1. AIM-Harvard/foundation-cancer-image-biomarker AIM-Harvard/foundation-cancer-image-biomarker Public

    Code and evaluation repository for the paper

    Jupyter Notebook 67 8

  2. project-lighter/lighter project-lighter/lighter Public

    Config-based framework for organized and reproducible deep learning. MONAI Bundle + PyTorch Lightning.

    Python 19 2

  3. ganslate-team/ganslate ganslate-team/ganslate Public

    Simple and extensible GAN image-to-image translation framework. Supports natural and medical images.

    Python 33 3

  4. EnlightenGAN EnlightenGAN Public

    Forked from VITA-Group/EnlightenGAN

    [Preprint] "EnlightenGAN: Deep Light Enhancement without Paired Supervision" by Yifan Jiang, Xinyu Gong, Ding Liu, Yu Cheng, Chen Fang, Xiaohui Shen, Jianchao Yang, Pan Zhou, Zhangyang Wang

    Python 10 2

  5. dense-depth-body-parts dense-depth-body-parts Public

    Forked from ashafaei/dense-depth-body-parts

    Dense classification of the depth images to recognize the body parts.

    Python 19 8