Open AccessAutomated marker identification using the Radon transform for watershed segmentation
Author(s) -
GonzálezBetancourt Aniel,
RodríguezRibalta Patricia,
MenesesMarcel Alfredo,
SifontesRodríguez Sergio,
LorenzoGinori Juan Valentín,
OrozcoMorales Rubén
Publication year - 2017
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2016.0525
Subject(s) - watershed , identification (biology) , radon transform , radon , artificial intelligence , segmentation , computer science , image segmentation , computer vision , pattern recognition (psychology) , physics , botany , quantum mechanics , biology
The automated identification of markers in medical imaging is one of the issues proposed in recent years for many tasks with wide application in digital image analysis, but there is no universal algorithm for this. We introduce here a low computational cost system based on the Radon transform (RT) to determine markers for watershed segmentation purposes in nearly circular structures of grey‐scale images such as the red blood cells in images obtained by optical light microscopy of blood smears. The search for markers is performed based on the ability of the RT to detect shape parameters and characterise their behaviour in circular structures. The circular structure edge was determined previously in order to apply the direct RT and after that the sinogram projections were filtered utilising a matched filter. Then, an image with peaks close to the circular structures' centres is obtained by means of the reverse RT. After this, a threshold is calculated and applied in order to identify the markers. The reached precision was 97.4%, which is comparable with results within the state of the art, and the F‐measure was 0.925.