//----------------------------------------------------------------------------------
//! Main routine.
//----------------------------------------------------------------------------------
void SegmentationEvaluationMetric::_process()
{
ML_TRACE_IN("SegmentationEvaluationMetric::_process ()");
_numTruePositive = 0;
_numTrueNegative = 0;
_numFalsePositive = 0;
_numFalseNegative = 0;
double sensitivity = 0.0;
double specificity = 0.0;
unsigned int numVoxels = 0;
double prevalence = 0.0;
double levelOfTest = 0.0;
double dsc = 0.0;
double cFactor = 0.0;
// process all pages
MLErrorCode err = processAllPages(-1);
if (err==ML_RESULT_OK) {
// sensitivity
if ( (_numTruePositive + _numFalseNegative) > 0) {
sensitivity = _numTruePositive / (double)(_numTruePositive+_numFalseNegative);
}
// specificity
if ( (_numTrueNegative + _numFalsePositive) > 0) {
specificity = _numTrueNegative / (double) (_numTrueNegative+_numFalsePositive);
}
// total number of voxels
numVoxels = _numTruePositive + _numFalsePositive + _numFalseNegative + _numTrueNegative;
// prevalence
if (numVoxels > 0) {
prevalence = (_numTruePositive + _numFalseNegative) / (double)numVoxels;
}
// level of test
if (numVoxels > 0) {
levelOfTest = (_numTruePositive + _numFalsePositive) / (double)numVoxels;
}
// Dice similarity coefficient
if ( 2*_numTruePositive + _numFalsePositive + _numFalseNegative > 0) {
dsc = 2.0 * _numTruePositive / (double)(2.0*_numTruePositive + _numFalsePositive + _numFalseNegative);
}
// C-Factor
double p = sensitivity;
double q = specificity;
double d = (2.0 * p * (1 - q)) / (p + (1-q)) + (2 * (1-p) * q) / ((1-p) + p);
if ( (p >= q) && (p > 1-q) ) {
cFactor = d;
}
else if ( (p < q) && (p > 1-q) ) {
cFactor = -d;
}
else if ( (p <= 1-q) ) {
// undefined
}
}
else {
// Set error status.
std::cerr << MLGetErrorCodeDescription(err);
}
// set output
_truePositiveFld->setIntValue(_numTruePositive);
_trueNegativeFld->setIntValue(_numTrueNegative);
_falsePositiveFld->setIntValue(_numFalsePositive);
_falseNegativeFld->setIntValue(_numFalseNegative);
_sensitivityFld->setDoubleValue(sensitivity);
_specificityFld->setDoubleValue(specificity);
_prevalenceFld->setDoubleValue(prevalence);
_levelOfTestFld->setDoubleValue(levelOfTest);
_diceSimilarityCoefficientFld->setDoubleValue(dsc);
_cFactorFld->setDoubleValue(cFactor);
}
//----------------------------------------------------------------------------------
//! Handle field changes of the field \c field.
//----------------------------------------------------------------------------------
void CalcCodedSegmentation::handleNotification (Field *field)
{
ML_TRACE_IN("CalcCodedSegmentation::handleNotification()")
if (field == _fld_Add)
{
replaceValues->clear();
replaceValues_MaxIndex = 0;
replaceValues->resize(MAX_SIZE,0);
addImage();
renewObjectValues();
int error = processAllPages(0);
if (error!=0) std::cout << "processAllPages Error (add) = " << MLGetErrorCodeDescription(error) << std::endl;
}
else if (field == _fld_Reset)
{
//std::cout << "_fld_Reset" << std::endl;
calcOutImageProps(0);
reset();
clearOutputImage();
getOutImg(0)->setOutOfDate();
int error = processAllPages(0);
if (error!=0) std::cout << "processAllPages Error (reset) = " << MLGetErrorCodeDescription(error) << std::endl; //Das mit dem invalidieren per setOutOfDate geht nicht
_fld_ObjectValues->setStringValue("");
_fld_ImageValues->setStringValue("");
