lar-running-demo

A demo beta software (set of scripts) to extract models from medical images. First step is image segmentation by Lisa software.

Spftware has been tested on Ubuntu 14.04 LTS (x64).

MIT License.

Install

Install PyPlasm

Download LAR somewhere in your home directory. It will be found automatically.

sudo apt-get install python-scipy python-numpy python-matplotlib\
    python-dicom cython python-pip

pip install larVolumeToObj

Sample data

https://github.com/mjirik/larVolumeToObj/blob/master/tests/nrn4.pklz?raw=true

http://147.228.240.61/queetech/sample-data/biodur_sample.zip

Library

import larVolumeToObj
larVolumeToObj.computation.pklzToSmoothObj.makeSmooth('nrn4.pklz', visualization=True)

Another exaples

V, F = larVolumeToObj.computation.pklzToSmoothObj.makeSmooth('nrn4.pklz')
larVolumeToObj.computation.visualization.visualize(V, F, explode=True)
larVolumeToObj.computation.visualization.visualizeObj('output/out_sm_i_tr.obj', explode=True)

Prepare DICOM or pklz data

import larVolumeToObj
import larVolumeToObj.computation.data_preparation as dp
dp.preparedata('tests/nrn4.pklz', 'nrn4_crop.pklz', crop=[[1, 6], [1, 6], [1, 6]], threshold=4400, visualization=True)

More complex example - prepare, smooth and show

import larVolumeToObj
larVolumeToObj.computation.data_preparation.preparedata(
    "./biodur_sample/",
    'biodur_crop.pklz',
    crop=[[1, 25], [200, 225], [200, 225]],
    threshold=1400)
V, F = larVolumeToObj.computation.pklzToSmoothObj.makeSmooth(
    'biodur_crop.pklz',
    bordersize=[5, 5, 5])
larVolumeToObj.computation.visualization.visualize(V, F, explode=False)

Commandline tools

data_preparation.py

Simple data preprocessing tool. Allows cropping and thresholding.

python data_preparation.py -i "tests/nrn4.pklz" -o prepared.pklz -threshold 4000 --visualization

python data_preparation.py -i "biodur_sample/" -o prepared_biodur.pklz -c 1 40 200 250 200 250 -t 1400

python data_preparation.py --help

volumeToObj.py

Extracts volume from pklz file or dicomdir

python volumeToObj -i nrn4.pklz -od outdir -v

visualize.py

Make visualization of objfile using Plasm

python visualize.py -i outdir/out.obj

visualize.sh

Given a Wavefront STL model (obj) it will show it using available on system visualizers.

Supported visualizers: PyPlasm, MeshLab, Manta

Two type of executions:

• Interactive
• Command Line (use -h to know the exact paramaters)