MICLab wins prize at the The 17th International Symposium on Medical Information Processing and Analysis

Our work on Multitasking segmentation of lung and COVID-19 findings in CT scans using modified EfficientDet, UNet and MobileNetV3 models received the SIPAIM award this year! Congratulations to the authors, Diedre Carmo, Israel Campiotti, Irene Fantini, Livia Rodrigues, Leticia Rittner and Roberto Lotufo. You can use our tool to create segmentations with the methodology published in this work here: https://github.com/MICLab-Unicamp/coedet    
Back To List

Leave a comment

Filtered HTML

  • Web page addresses and e-mail addresses turn into links automatically.
  • Allowed HTML tags: <a> <em> <strong> <cite> <blockquote> <code> <ul> <ol> <li> <dl> <dt> <dd>

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.

Share MICLab´s content!

Here you can read MICLab´s exclusive articles on medical imaging, computer programming and MRI analysis. You are welcome to share these blog posts freely, but keep in mind always to cite MICLab and this webaddress as the source!