Classification and quantification based on image analysis for sperm samples with uncertain damaged/intact cell proportions

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5112 LNCS, Issue , 2008, Pages 827-836

  Sánchez, Lidia ^a   González, Víctor ^a   Alegre, Enrique ^a   Alaiz, Rocío ^a  

^a UNIVERSITY OF LEÓN   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); COMPUTER VISION; DISCRETE WAVELET TRANSFORMS; ELECTRIC FAULT CURRENTS; ERROR ANALYSIS; IMAGE ANALYSIS; IMAGE PROCESSING; IMAGE SEGMENTATION; IMAGING TECHNIQUES; NEURAL NETWORKS; STANDARDS; WAVELET TRANSFORMS;

BACK PROPAGATION NEURAL NETWORK (BPANN); CLASS DISTRIBUTIONS; DAMAGED CELLS; DESCRIPTORS; DESIGN CONDITIONS; DISCRETE WAVELETS; ERROR RATE (ER); HEIDELBERG (CO); INTACT CELLS; INTERNATIONAL CONFERENCES; MEAN ABSOLUTE ERROR (MAE); MISCLASSIFICATION RATES; QUANTIFICATION METHODS; REGION -OF-INTEREST (ROI); SPERM CELLS; STANDARD DEVIATION (STD);

CELLS;

EID: 47749100121     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-69812-8_82     Document Type: Conference Paper

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