nmjanalyzer 0.0.3

NMJ Analyzer

NMJ_Analyser

The code was created using python 3.7 and the following version of packages

Requirements

• scipy 1.5.3
• Pillow 7.2.0
• numpy 1.19.1
• pandas 1.1.0
• nibabel 3.1.1

In addition, the following modules are imported

• glob
• os
• argparse
• sys

Performs analysis of NMJ data

Usage

The NMJ Analyser takes as input directories where jpg files have been stored

For each subject, the input is presented as SUBJ/JPEG/*jpg The ..... files must contain the keyword red or RED The ..... files must contain the keyword green or GREEN The slices should ordered numerically ex Mouse1_GREEN_0001.jpg.... Mouse1_GREEN_0010.jpg

The following parameters are given to the system:

• -p regular expression of the subject path
• -dx planar resolution
• -dz slice thickness
• -t threshold for voxels to be considered as positives

Output

For each subject the following parameters are calculated for each RED connected component and intersection of GREEN on RED component

RegionProperties

• 'centre of mass': (self.centre_of_mass, ['CoMx', 'CoMy', 'CoMz']),
• 'centre_abs': (self.centre_abs, ['Truex, Truey, Truez']),
• 'volume': (self.volume, ['NVoxels', 'NVolume']),
• 'fragmentation': (self.fragmentation, ['Fragmentation']),
• 'mean_intensity': (self.mean_int, ['MeanIntensity']),
• 'surface': (self.surface, ['NSurface', 'Nfaces_surf', 'NSurf_ext', 'Nfaces_ext']),
• 'surface_dil': (self.surface_dil, ['surf_dil', 'surf_ero']),
• 'surface volume ratio': (self.sav, ['sav_dil', 'sav_ero']),
• 'compactness': (self.compactness, ['CompactNumbDil' ]),
• 'eigen': (self.eigen, ['eigenvalues']),
• 'std': (self.std_values, ['std']),
• 'quantiles': (self.quantile_values, ['quantiles']),
• 'bounds': (self.bounds, ['bounds']),
• 'cc': (self.connect_cc, ['N_CC']),
• 'cc_dist': (self.dist_cc, ['MeanDistCC']),
• 'cc_size': (self.cc_size, ['MinSize', 'MaxSize', 'MeanSize']),
• 'max_extent': (self.max_extent, ['MaxExtent']),
• 'shape_factor': (self.shape_factor, ['ShapeFactor', 'shapefactor_surfcount']),
• 'skeleton_length': (self.skeleton_length, ['SkeletonLength'])

Comparison Properties

• 'green volume': (self.n_pos_ref, 'Volume_(Green)'),
• 'red volume': (self.n_pos_seg, 'Volume_(Red)'),
• 'n_intersection': (self.n_intersection, 'Intersection'),
• 'n_union': (self.n_union, 'Union'),
• 'IoU': Intersection of union
• 'coverage': Overlap
• 'vol_diff': Volume difference
• 'ave_dist': Average distance
• 'haus_dist': Hausdorff distance
• 'haus_dist95': 95% HD
• 'com_dist': distance between centre of mass
• 'com_ref': centre of mass RED
• 'com_seg': centre of mass GREEN