[Automated detection of spleen volume by spiral CT scans using neural networks and "fuzzy logic"].
OBJECTIVE
To assess spleen segmentation and volumentry in spiral CT scans with and without pathological changes of splenic tissue.


METHODS
The image analysis software HYBRIKON is based on region growing, self-organized neural nets, and fuzzy-anatomic rules. The neural nets were trained with spiral CT data from 10 patients, not used in the following evaluation on spiral CT scans from 19 patients. An experienced radiologist verified the results. The true positive and false positive areas were compared in terms to the areas marked by the radiologist. The results were compared with a standard thresholding method.


RESULTS
The neural nets achieved a higher accuracy than the thresholding method. Correlation coefficient of the fuzzy-neural nets: 0.99 (thresholding: 0.63). Mean true positive rate: 90% (thresholding: 75%), mean false positive rate: 5% (thresholding > 100%). Pitfalls were caused by accessory spleens, extreme changes in the morphology (tumors, metastases, cysts), and parasplenic masses.


CONCLUSIONS
Self-organizing neural nets combined with fuzzy rules are ready for use in the automatic detection and volumetry of the spleen in spiral CT scans.
Heitmann
K R
KR
Klinik und Poliklinik für Radiologie, Johannes Gutenberg-Universität Mainz. kauczor@radiologie.klinik.uni-mainz.de
Rückert
S
S
Heussel
C P
CP
Uthmann
T
T
Thelen
M
M
Kauczor
H U
HU
D000328:Adult; D000368:Aged; D003560:Cysts / Q000000981:diagnostic imaging; D005189:False Positive Reactions; D005260:Female; D017143:Fuzzy Logic; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D015203:Reproducibility of Results; D012984:Software; D013154:Spleen / Q000002:abnormalities / Q000033:anatomy & histology* / Q000000981:diagnostic imaging*; D013158:Splenic Diseases / Q000000981:diagnostic imaging*; D013160:Splenic Neoplasms / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods*