MrGiovanni / MrGiovanni/ModelsGenesis
segmentation accuracy of lung nodule on LUNA16
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- Jupyter Notebook
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Description
I crop lung nodule to 646464 and turn the gray level to [0,255], and then turn it to [0,1] as the input of UNet3D. I used the pre-trained weight excluded the final_layer, and I replaced it as a two channels output (for one-hot output). But I found that I can't get a better initial weight than my UNet3D trained using random initial. I wonder if the operation that I replace the final_layer is wrong. I hope that I can get your help.
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Research direction
Review the UNet3D model definition around final_layer and the pre-trained-weight loading path, then reproduce the LUNA16 64×64×64 preprocessing and two-channel fine-tuning setup. Compare initialization behavior against random initialization and document whether the replacement and loading sequence preserves the pretrained weights or identify the mismatch.
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Assessment
- Tech stack
- jupyter-notebook, keras, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100