Comments (9)
Ank-22
commented on July 21, 2024
@ranjeetds I have started downloading the data set the total size is 22.3GB, Download size 13.3 GB. As soon as it is downloaded the I will temper around it and understand the data, As it is images we will go for CNN or DCNN
from osic-pulmonary-fibrosis-progression.
Ank-22
commented on July 21, 2024
Make A notebook and do virtualization of the dataset
from osic-pulmonary-fibrosis-progression.
Ank-22
commented on July 21, 2024
Images file type is .dcm @ranjeetds
from osic-pulmonary-fibrosis-progression.
ranjeetds
commented on July 21, 2024
https://stackoverflow.com/questions/53707851/using-dicom-images-with-opencv-in-python
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Ank-22
commented on July 21, 2024
I am Following this one: https://pydicom.github.io/pydicom/stable/auto_examples/input_output/plot_read_dicom.html
from osic-pulmonary-fibrosis-progression.
Ank-22
commented on July 21, 2024
https://www.kaggle.com/c/osic-pulmonary-fibrosis-progression/discussion/165723 @ranjeetds Look into this
from osic-pulmonary-fibrosis-progression.
Ank-22
commented on July 21, 2024
https://www.kaggle.com/c/osic-pulmonary-fibrosis-progression/discussion/165723 @ranjeetds Look into this
A Bit Helpful for some of the image data
from osic-pulmonary-fibrosis-progression.
ranjeetds
commented on July 21, 2024
looks like we need to download data again - v2
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Ank-22
commented on July 21, 2024
NO sir, we need to perform an image augmentation, He has provided the code of
pydicom.SliceThickness
https://www.kaggle.com/wcukierski/testing-reading-of-id00011637202177653955184
from osic-pulmonary-fibrosis-progression.
Related Issues (17)
- Make A notebook and do virtualization of the dataset HOT 1
- ResNet Approach HOT 2
- AutoEncoder Apporach HOT 2
- Custom Approach HOT 1
- Try Advance Visualization & Patient & Week Wise HOT 1
- Make Reading Material for ResNet HOT 1
- Start with readme
- Make AutoEncoder.MD
- Write A script for AutoEncoder
- Train the autoencoder
- Let's have Brainstorming Meet HOT 3
- Added How to Implement the ResNet
- Add the Win / Judging criteria in read me
- Decide a Approach HOT 7
- Add Some Reading Material HOT 3
- Create Subset Dataset HOT 6
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