MCI-frcnn

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Simon Zhongyuan Tian*, Pengfei Yin, Kai Jing, Yang Yang, Yewen Xu, Guangyu Huang, Duo Ning, Melissa J. Fullwood*, and Meizhen Zheng*. 2022. “MCI-Frcnn: A Deep Learning Method for Topological Micro-Domain Boundary Detection.” Frontiers in Cell and Developmental Biology 10 (November): 1050769. https://doi.org/10.3389/fcell.2022.1050769.

• MC-frcnn is a deep learning based object detector used for micro-domain boundary detection.
• MCI-frcnn derived Faster R-CNN with modifications from https://github.com/kbardool/keras-frcnn.

Enviroment

Ubuntu==16.06
python==3.6.13
tensorflow==2.2.0
keras==2.3.1
opencv==3.4.2
h5py==2.10.0

1. Using (LabelMe) to draw ground truth boundary of micro-domains

SH00.rename.image.and.json.sh
SH02.run.json2anno.sh

2. Training RPN with script:

SH10.run.training.sh

3. Detecting micro-domain using script:

SH11.run.detecting.sh

4. Formating micro-domain coordinates

SH12.sta.sh
SH13_FILTER_ANNO.py
SH15_COOR_PIC_CONNECT.py
SH30.adjustanno.sh

5. Mesuare traing quality

SH32.run.measure.sh