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mikejhuang / LungNoduleDetectionClassification

Automated Extraction and Classification of Pulmonary Lung Nodules from CT Scans
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TrainUnet #8

Open abinramapuram opened 4 years ago

abinramapuram commented 4 years ago

I have done segmentation training with lung images and mask nodules using 2trainUnet.ipynb. But when check with test images, It just segments the lung portion, not the nodule. Did you got the nodule segmentation with the TrainUnet??

mikejhuang commented 4 years ago

Yes, it segments the nodules. Check your labels to make sure you're training with the nodules and not the lung mask.

On Tue, Mar 3, 2020 at 2:46 PM Abin Abraham Oommen notifications@github.com wrote:

I have done segmentation training with lung images and mask nodules using 2trainUnet.ipynb. But when check with test images, It just segments the lung portion, not the nodule. Did you got the nodule segmentation with the TrainUnet??

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abinramapuram commented 4 years ago

Thank you for the fast response. I have already taken the nodule masks. Number of patient samples taken is less, 30 only. Should it be the reason?? What is difference between nodulemasks and nodulemaskscircle??

mikejhuang commented 4 years ago

See the tutorial for better understanding of the pipeline. https://www.kaggle.com/c/data-science-bowl-2017/overview/tutorial

On Tue, Mar 3, 2020 at 6:42 PM Abin Abraham Oommen notifications@github.com wrote:

Thank you for the fast response. I have already taken the nodule masks. Number of patient samples taken is less, 30 only. Should it be the reason?? What is difference between nodulemasks and nodulemaskscircle??

— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/mikejhuang/LungNoduleDetectionClassification/issues/8?email_source=notifications&email_token=ACTAYDBKHOM7J3EVAXOD5XTRFTNJVA5CNFSM4LADTCUKYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOENS7FTI#issuecomment-593883853, or unsubscribe https://github.com/notifications/unsubscribe-auth/ACTAYDB4E4ZQPKUURV6I363RFTNJVANCNFSM4LADTCUA .