Inspiration
We signed up to take part of this unique project and to contribute to the implementation of the automatic seed detection that could potentially have a significant clinical impact on patient's experience and on their quality of life.
What it does
By using state of the art dee learning architectures, it identifies the position of the seeds on a 3 dimensional CT-Scans.
How we built it
By using tutorials given on workshops, and with help of some McMed technicians
Challenges we ran into
running sessions on Jupyter(buggs), installing some libraries, understanding the code and its architecture
Accomplishments that we're proud of
- staying until the end
- struggled while some of the tasks
- team work synergy ## What we learned
- r-CNN architecture, python libraries (exemple forger) ## What's next for AutomaticSeedDetection
- we have a plan
- reading more, finishing coding and having our results.
Built With
- english-arabic
- forger
- jupyter
- mcmedhacksworkshop
- pandas
- python
- scikit-learn
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