openTMAS

openTMAS: Open-source Targeted Medical Images Analysis System

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Project maintained by notagenius Hosted on GitHub Pages — Theme by mattgraham

Welcome to openTMAS project progress page.

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Progress Milestones (May - June):

• Dataset Research
  • X-Ray
    • covid related ✔️ Link to our report (updated on 27 May 2020)
    • general conditions ✔️ (May 2020) Link to our report (updated on 27 May 2020)
• Medical Learning Schedule
  • radiopaedia 2020 4-day vitual conference (chest images on Day 2) Link to conference schedule (23 June)
  • read covid cases on Eurorad ✔️ Link to cases (updated on 30 May 2020, all 22 items are read)
  • read covid case on Sirm Link to cases (in Italian, translator needed)
• Artificial Intelligence Study
  • Lung Segmentation
    • Algorithms ✔️ Link to our report (updated on 02 June 2020)
    • Experiment Round 1 with implementing UNet ✔️ Link to our code (updated on 10 June 2020)
  • Lung Reconstruction
    • Algorithms
  • Lung Image Classification / Regression
    • Algorithms
• Web App
  • Frontend UI Design ✔️
  • Backend Endpoint Design

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Implementation Result

• (updated on May 2020) the visualization of predicted lung segmentation from deep learning based U-Net implementation. [code]

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openTMAS Library

• the paper collection

• book: Deep Learning by Ian Goodfellow

• book: Neural Networks and Deep Learning by Michael Nielsen

• book: Pneumonia essentials by Burke A. Cunha

• book: Chest Radiology: The Essentials by Jannette Collins MD MEd

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The team includes [Marcel, the developer and designer] [Weiling, the data scientist] and this project is under the supervision of Tim. [Tim, experienced manager of digitization]

contact us:

• marcel.ochsendorf@gmail.com
• aileen365@gmail.com

© 2020. All rights reserved.