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A framework for Medical Image Segmentation with Convolutional Neural Networks and Deep Learning

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The overall pipeline looks the same except some minor details: ``` # Library import from miscnn.processing.preprocessor import Preprocessor # Create and configure the Preprocessor class pp = Preprocessor(data_io, data_aug=data_aug, batch_size=2,...

bug

Hello!! I tried to predict a new CT Image with the code below: The prediction image do generate, but I can't open those in a software like 3D slicer! What...

enhancement

Hi, first of all thanks for this framework, it is very useful. I had a question regarding the notebook for the DICOM example under "./examples/LCTSC_DICOMInterface.ipynb" what is the need of...

bug
question

Hi! Just to confirm, is MIScnn compatible with tensorflow-serving for model deployment? Thanks in advance!

information

Hi, Regardless of its dice_soft, the orientation of all predicted segmentations with NIFTI file format was different from the ground truth. I tried to fix dicom_io.py, but I could not...

wontfix

Using the example kidney data, we have confirmed that learning is possible. And I am trying to learn using my data, but it does, but the loss does not drop....

question

In the `fullimage` mode I get this on predicting a batch: ``` --------------------------------------------------------------------------- ValueError Traceback (most recent call last) in ----> 1 model.predict(sample_list[0:2]) ~\anaconda3\envs\bacteria_cfu\lib\site-packages\miscnn\neural_network\model.py in predict(self, sample_list, return_output, activation_output) 168...

bug

Hi, I noticed the links provided for the papers associated to the Compact and Dense U-Net architectures are wrong. Both links are pointing to the ResNet paper "[Deep Residual Learning...

enhancement

Hi, I think my problem related more to basic concepts of deep learning than to your specific project, but I'm not really sure. My problem is that after several experiments...

Add a Pipeline Element that applies merges multiple models into a result. To merge different folds for example. Potentially allow for multiple functions like Linear combination, Polynominal combination or class...

enhancement