Pulmonary
Nodule Analysis Applications
Several
Image analysis applications are available on the system for the analysis of
chest and cardiac CT images. 
Image nodule
detectors 
| 
   vmonodule  | 
  
   This application runs
  the MONAI lung nodule detection algorithm  | 
 
| 
   vtsnodule  | 
  
   Runs the TotalSegmentator (Bluemind)
  nodule detection algorithm  | 
 
           
These applications
have the following Syntax
<application> [if=]<input> [of=]output [od=<output-directory>] [-ic] [-csv]
Nodule
csv file output:
The output of
the nodule detectors is a csv file with the following columns
| 
   Column Heading  | 
  
   Contents  | 
 
| 
   image  | 
  
   image-code of the analyzed image  | 
 
| 
   nodule  | 
  
   a numeric nodule identifier (starts at 1)  | 
 
| 
   x  | 
  
   x coordinate of nodule center in pixels  | 
 
| 
   y  | 
  
   y coordinate of nodule center in pixels  | 
 
| 
   z  | 
  
   z coordinate of nodule center in pixels  | 
 
| 
   prob  | 
  
   probability that the entity is a pulmonary nodule  | 
 
| 
   size  | 
  
   estimation of the diameter of the nodule in mm  | 
 
| 
   xs  | 
  
   x-dimension extent of the nodule in pixels  | 
 
| 
   ys  | 
  
   y-dimension extent of the nodule in pixels  | 
 
| 
   xs  | 
  
   z-dimension extent of the nodule in pixels  | 
 
The main program for providing input to the pulmonary nodule classifier is vnodext which has the following syntax:
                vnodext 
 [if=]<original-image> in=<nodule-csv-file> [of=][output directory] [-ic]
When the -ic option is specified the image original-image is specified
by just the image-code. Note, this algorithm is define
for a single image analysis only. A csv file from a batch run must be partitioned
into individual image-code sets of rows for analysis. 
The following experimental programs for nodule analysis are currently available:
| 
   vnodext  | 
  
   Extract the nodule regions
  from the original image and creates individual 32 x 32 x 32 images for
  malignancy evaluation. For classification the nodules are magnified by
  interpolation to occupy most of the space in the image. Actual unmagnified images
  can also be created for visualization.   | 
 
| 
   vnodvis  | 
  
   Create a visualization version of the original image in which the regions of all detected nodules are clearly visible. Input parameters are similar to vnodext  | 
 
| 
   vnview  | 
  
   The images that result
  from vnodext are windowed and tiled into a 6
  x 6 grid for convenient visualization. The input is a 32 x 32 x 32 nodule
  region image created by vnodext.  | 
 
| 
   vnnview  | 
  
   Apply vnview to all images in a directory  |