Spatial second-derivative image processing: an application to optical mammography to enhance the detection of breast tumors.
We present an image-processing method that enhances the detection of regions of higher absorbance in optical mammograms. At the heart of this method lies a second-derivative operator that is commonly employed in edge-detection algorithms. The resulting images possess a high contrast, an automatic display scale, and a greater sensitivity to smaller departures from the local background absorbance. Moreover, the images are free of artifacts near the breast edge. This second-derivative method enhances the display of structural information in optical mammograms and may be used to robustly select areas of interest to be further analyzed spectrally to determine the oxygenation level of breast lesions.
Pera
Vivian E
VE
Tufts University, Bioengineering Center, Department of Biomedical Engineering, 4 Colby Street, Medford, Massachusetts 02155, USA.
Heffer
Erica L
EL
Siebold
Horst
H
Schutz
Oliver
O
Heywang-Kobrunner
Sylvia
S
Gotz
Linda
L
Heinig
Anke
A
Fantini
Sergio
S
D000368:Aged; D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis / Q000473:pathology*; D018270:Carcinoma, Ductal, Breast / Q000175:diagnosis / Q000473:pathology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008327:Mammography / Q000379:methods; D008875:Middle Aged; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D041622:Tomography, Optical / Q000379:methods*