Report of Kaggle Competition(GaHoBe-Gayathri, HongKee, Benoit)

Scientific Computing FacilityHongKee Moon (moon@mpi-cbg.de)5th Nov. 2018

1 Scientific Computing Facility@MPI-CBG

2018 Data Science Bowl

• Mission: Nuclei detection automation1

• By using Deep-learning API• Python preferable

• Our approach• Keras (tensorFlow backend) / U-Net• Fiji• Parameter optimization

1 https://www.kaggle.com/c/data-science-bowl-2018

2 Scientific Computing Facility@MPI-CBG

Pipeline

1. Training a model - U-net2. Testing the model on the problem set3. Submission and post the score

Requirements1. python: numpy, skimage, keras2. fiji: image processing3. keras: deep learning

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Training a model

1. input: 512x512x3 8bit, output: 512x512 boolean2. preprocessing resize, boundary weights, masks3. loss function, accuracy function for optimizer4. U-net networks5. fitting the model

6. check IoU2 results2 https://www.pyimagesearch.com/2016/11/07/intersection-over-union-iou-for-object-detection/

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Testing the model on the problem set

• Preprocess images with fillholes and watershed• Input image resize to 512x512• Predict masks with the model• Upscale the mask images with the original size after postprocesing

(e.g. fill holes)

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Submission the results

• Result format

• RLE encoding: Run-length encoding3

• Check the leaderboard• Public Leader Board

• Our score is 0.419 in 2nd stage while Benoit achieve better after competition

3 https://www.kaggle.com/rakhlin/fast-run-length-encoding-python

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Better approaches from other teams• No 1. [ods.ai] topcoders: IoU = 0.631

• Solution description: https://www.kaggle.com/c/data-science-bowl-2018/discussion/54741• github: https://github.com/selimsef/dsb2018_topcoders/

• Unet Nuke: IoU = 0.545• Solution description: https://www.kaggle.com/c/data-science-bowl-2018/discussion/54742• github: https://github.com/nicolefinnie/kaggle-dsb2018

• Image Data sets to train• Broad Bioimage Benchmark Collection https://data.broadinstitute.org/bbbc/image_sets.html• Image Data Resource https://idr.openmicroscopy.org/about/index.html

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Future plans discussed• Web site for pre-test nuclei detection before consulting to Bio-

image informatics• User can submit training data with annotation• Improve the model and make the better prediction periodically• Easily change the model based on the problem context

• Flywing, neuron, etc

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Demo !9 Scientific Computing Facility@MPI-CBG