An approach to automatically localize and find the shapes of tumors and other stiff inclusions.
962
Code for the ICRA2018 paper Trajectory-Optimized Sensing for Active Search of Tissue Abnormalities in Robotic Surgery.
The code folder contains two folders; discrete_probing and continuous_probing.
Fig.3 in the paper.demo.m file for generating stiffness map using all the algorithms discussed the paper.incremental_demo.m file for generating stiffness map using all the algorithms discussed the paper in an incremental fashion (you can see the points being probed sequentially). This code also saves all the results at after each probe in an automatically generated results folder.recall_plot_randomized_groundTruths.m and recall_plot_same_groundTruth.m files to generate the recall plot of Fig. 4.Fig.5 in the paper.test.m file for generating stiffness map using any of the algorithms discussed the paper (you can change which algorithm you want to test inside the code)demo.m file for generating stiffness map using all the algorithms discussed the paper. This code also saves all the results at after each probe in an automatically generated results folder.recall_plot_randomized_groundTruths.m and recall_plot_same_groundTruth.m files to generate the recall plot of Fig. 8.Tested on Ubuntu 16.04.6 with Docker 18.06.1-ce, MATLAB R2017a.
docker run --rm -p 8888:8888 -v /usr/local/MATLAB/R2017a:/usr/local/MATLAB/R2017a \
-v /usr/local/lib/python3.5/dist-packages/matlab:/usr/local/lib/python3.5/dist-packages/matlab \
--mac-address=2c:60:0c:d6:50:36 icra2018/trajectory-optimized-active-search:latest
Content type
Image
Digest
Size
327 MB
Last updated
over 7 years ago
docker pull icra2018/trajectory-optimized-active-search