DocumentCode :
1395257
Title :
Computer-aided detection of breast cancer nuclei
Author :
Schnorrenberg, Frank ; Pattichis, Constantinos S. ; Kyriacou, Kyriacos C. ; Schizas, Christos N.
Author_Institution :
Dept. of Comput. Sci., Univ. of Cyprus, Nicosia, Cyprus
Volume :
1
Issue :
2
fYear :
1997
fDate :
6/1/1997 12:00:00 AM
Firstpage :
128
Lastpage :
140
Abstract :
A computer-aided detection system for tissue cell nuclei in histological sections is introduced and validated as part of the Biopsy Analysis Support System (BASS). Cell nuclei are selectively stained with monoclonal antibodies, such as the anti-estrogen receptor antibodies, which are widely applied as part of assessing patient prognosis in breast cancer. The detection system uses a receptive field filter to enhance negatively and positively stained cell nuclei and a squashing function to label each pixel value as belonging to the background or a nucleus. In this study, the detection system assessed all biopsies in an automated fashion. Detection and classification of individual nuclei as well as biopsy grading performance was shown to be promising as compared to that of two experts. Sensitivity and positive predictive value were measured to be 83% and 67.4%, respectively. One major advantage of BASS stems from the fact that the system simulates the assessment procedures routinely employed by human experts; thus it can be used as an additional independent expert. Moreover, the system allows the efficient accumulation of data from large numbers of nuclei in a short time span. Therefore, the potential for accurate quantitative assessments is increased and a platform for more standardized evaluations is provided.
Keywords :
image classification; image enhancement; medical image processing; BASS; Biopsy Analysis Support System; accurate quantitative assessment; anti-estrogen receptor antibodies; biopsy grading performance; breast cancer; computer-aided detection system; histological sections; monoclonal antibodies; patient prognosis assessment; pixel value labeling; positive predictive value; receptive field filter; selective staining; sensitivity; squashing function; standardized evaluations; tissue cell nuclei; Biopsy; Breast cancer; Cancer detection; Diseases; Filters; Genetics; Humans; Immune system; Nervous system; Tumors; Algorithms; Breast Neoplasms; Cell Nucleus; Diagnosis, Computer-Assisted; Female; Humans; Receptors, Estrogen; Receptors, Progesterone;
fLanguage :
English
Journal_Title :
Information Technology in Biomedicine, IEEE Transactions on
Publisher :
ieee
ISSN :
1089-7771
Type :
jour
DOI :
10.1109/4233.640655
Filename :
640655
Link To Document :
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