BRISC::Core::MarkovRandom Class Reference

Performs Markov random field operations on a LIDCNodule. More...

List of all members.

Static Public Member Functions

static void PerformMarkov (LIDCNodule nodule)
 Performs Markov analysis on the given nodule and saves the results to the appropriate LIDCNodule fields.
static double[][,] FindParameters (int[,] segData)
 Finds the MRF parameters.

Static Public Attributes

static double histMinVal = 0
 Minimum value for histogam binning. All values below this will be binned into the bottom bin.
static double histMaxVal = 0
 Maximum value for histogram binning. All values above this will be binned into the top bin.
static int binSize = 512
 Number of bins in the response histograms.

Static Private Member Functions

static void normalize (ref int[,] segData)
 Normalizes the image with zero mean.
static void deriveNewFeatures (int[,] segData, int x, int y, int pad, ref double[][,] markovParams)
 Calculates new features from the beta parameters.
static void calcSumCorrVect (int[,] segData, int x, int y, ref GeneralMatrix sum_corr, ref GeneralMatrix sum_vector)
 Function calculates the sum of the correlation and vectors.
static double calcSumVar (int[,] segData, int x, int y, ref GeneralMatrix parameters)
 Sums up the variances and the first part of the beta parameter.

Static Private Attributes

static int pad = 4
 Padding needed around the image.


Detailed Description

Performs Markov random field operations on a LIDCNodule.

markov.png


Member Function Documentation

static void BRISC::Core::MarkovRandom::calcSumCorrVect ( int  segData[,],
int  x,
int  y,
ref GeneralMatrix  sum_corr,
ref GeneralMatrix  sum_vector 
) [inline, static, private]

Function calculates the sum of the correlation and vectors.

Parameters:
segData Original image
x Current column index
y Current row index
sum_corr Matrix to store the sum of the correlation
sum_vector Matrix to store the sum of the vectors

static double BRISC::Core::MarkovRandom::calcSumVar ( int  segData[,],
int  x,
int  y,
ref GeneralMatrix  parameters 
) [inline, static, private]

Sums up the variances and the first part of the beta parameter.

Parameters:
segData Original image
x Current column index
y Current row index
parameters Matrix to store beta parameters
Returns:
Sum of the Variance

static void BRISC::Core::MarkovRandom::deriveNewFeatures ( int  segData[,],
int  x,
int  y,
int  pad,
ref double  markovParams[][,] 
) [inline, static, private]

Calculates new features from the beta parameters.

Parameters:
segData Original image
x Current column index
y Current row index
pad Padding around the image
markovParams Passed in as beta values. Returned as new features

static double [][,] BRISC::Core::MarkovRandom::FindParameters ( int  segData[,]  )  [inline, static]

Finds the MRF parameters.

Parameters:
segData Image to run calculations on
Returns:
Five MRF parameter matrices

static void BRISC::Core::MarkovRandom::normalize ( ref int  segData[,]  )  [inline, static, private]

Normalizes the image with zero mean.

Parameters:
segData Image to normalize
Results are worse if we normalize. Not sure why this is, reguardless we are not using this function. It's here just in case.

static void BRISC::Core::MarkovRandom::PerformMarkov ( LIDCNodule  nodule  )  [inline, static]

Performs Markov analysis on the given nodule and saves the results to the appropriate LIDCNodule fields.

Parameters:
nodule LIDCNodule to run Markov on


The documentation for this class was generated from the following file:
Generated on Wed Aug 16 17:13:32 2006 by  doxygen 1.4.7