Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Active Deep Learning for Medical Imaging Segmentation
| Date | Stars |
|---|---|
| 2026-07-31 | 280 |
| 2026-08-06 | 280 |
| 2026-08-07 | 280 |
| 2026-08-14 | 280 |
| 2026-08-15 | 280 |
| 2026-08-18 | 280 |
| 2026-09-16 | 280 |
| 2026-09-20 | 280 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# Active Deep Learning for Medical Imaging Segmentation
| ![Marc Górriz][MarcGorriz-photo] | ![Axel Carlier][AxelCarlier-photo] | ![Emmanuel Faure][EmmanuelFaure-photo] | ![Xavier Giro-i-Nieto][XavierGiro-photo] |
|:-:|:-:|:-:|:-:|
| [Marc Górriz][MarcGorriz-web] | [Axel Carlier][AxelCarlier-web] | [Emmanuel Faure][EmmanuelFaure-web] | [Xavier Giro-i-Nieto][XavierGiro-web] |
[MarcGorriz-web]: https://www.linkedin.com/in/marc-górriz-blanch-74501a123/
[XavierGiro-web]: https://imatge.upc.edu/web/people/xavier-giro
[AxelCarlier-web]: http://carlier.perso.enseeiht.fr
[EmmanuelFaure-web]: https://www.irit.fr/~Emmanuel.Faure/
[MarcGorriz-photo]: https://raw.githubusercontent.com/marc-gorriz/CEAL-Medical-Image-Segmentation/master/authors/MarcGorriz.jpg
[XavierGiro-photo]: https://raw.githubusercontent.com/marc-gorriz/CEAL-Medical-Image-Segmentation/master/authors/XavierGiro.jpg
[AxelCarlier-photo]: https://raw.githubusercontent.com/marc-gorriz/CEAL-Medical-Image-Segmentation/master/authors/AxelCarlier.jpg
[EmmanuelFaure-photo]: https://raw.githubusercontent.com/marc-gorriz/CEAL-Medical-Image-Segmentation/master/authors/EmmanuelFaure.png
A joint collaboration between:
| ![logo-vortex] | ![logo-enseeiht] | ![logo-gpi] |
|:-:|:-:|:-:|
| [IRIT Vortex Group][vortex-web] | [INP Toulouse - ENSEEIHT][enseeiht-web] | [UPC Image Processing Group][gpi-web] |
[vortex-web]: https://www.irit.fr/-VORTEX-Team-?lang=fr/
[enseeiht-web]: http://www.enseeiht.fr/fr/index.html/
[upc-web]: http://www.upc.edu/?set_language=en/
[etsetb-web]: https://www.etsetb.upc.edu/en/
[gpi-web]: https://imatge.upc.edu/web/
[logo-vortex]: https://raw.githubusercontent.com/marc-gorriz/CEAL-Medical-Image-Segmentation/master/logos/Vortex.png "VORTEX Team (IRIT)"
[logo-enseeiht]: https://raw.githubusercontent.com/marc-gorriz/CEAL-Medical-Image-Segmentation/master/logos/enseeiht.png "Institut National polytechnique de Toulouse (ENSEEIHT)"
[logo-gpi]: https://raw.githubusercontent.com/marc-gorriz/CEAL-Medical-Image-Segmentation/master/logos/gpi.png "UPC GPI"
## Abstract
We propose a novel Active Learning framework capable to train effectively a convolutional neural network for semantic segmentation of medical imaging, with a limited amount of training labeled data. Our contribution is a practical Cost-Effective Active Learning approach using Dropout at test time as Monte Carlo sampling to model the pixel-wise uncertainty and to analyze the image information to improve the training performance.
## Publication
ML4H: Machine Learning for Health Workshop at NIPS 2017, Long Beach, CA, USA, In Press. Find the pre-print version of our work on [arXiv](https://arxiv.org/abs/1711.09168).
Please cite with the following Bibtex code:
```
@article{DBLP:journals/corr/abs-1711-09168,
author = {Marc Gorriz and
Axel Carlier and
Emmanuel Faure and
Xavier {Gir{\'{o}} i Nieto}},
title = {Cost-Effective Active Learning for Melanoma Segmentation},
journal = {CoRR},
volume = {abs/1711.09168},
year = {2017},
url = {http://arxiv.org/abs/1711.09168},
archivePrefix = {arXiv},
eprint = {1711.09168},
timestamp = {Mon, 04 Dec 2017 18:34:59 +0100},
biburl = {http://dblp.org/rec/bib/journals/corr/abs-1711-09168},
bibsource = {dblp computer science bibliography, http://dblp.org}
}
```
## Slides
<centrate>
<iframe src="//www.slideshare.net/slideshow/embed_code/key/cadu74MspLHLW5" width="595" height="485" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" style="border:1px solid #CCC; border-width:1px; margin-bottom:5px; max-width: 100%;" allowfullscreen> </iframe> <div style="margin-bottom:5px"> <strong> <a href="//www.slideshare.net/xavigiro/active-deep-learning-for-medical-imaging" title="Active Deep Learning for Medical Imaging" targExcerpt of 7,522 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:34327b074dbab9f7, name:image segmentation