A Computational Study on Bacterial Cell Images
Digital Image Processing Techniques
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The book deals with the studies relating to the analysis of images of various bacterial cells, for Gram-staining characterization, identification, classification and cell growth phase analysis and cell division time determination. Several segmentation techniques, namely, color segmentation, edge-based segmentation, thresholding and active contour segmentations, have been used. The geometric features for cell regions are extracted. Different classification techniques, namely, 3 , K-NN, Neural Network, fuzzy and neuro-fuzzy classifiers, are used for automatic Gram-characterization, identificatio...
The book deals with the studies relating to the analysis of images of various bacterial cells, for Gram-staining characterization, identification, classification and cell growth phase analysis and cell division time determination. Several segmentation techniques, namely, color segmentation, edge-based segmentation, thresholding and active contour segmentations, have been used. The geometric features for cell regions are extracted. Different classification techniques, namely, 3 , K-NN, Neural Network, fuzzy and neuro-fuzzy classifiers, are used for automatic Gram-characterization, identification and classification of bacterial cells images, which assists the microbiologists for faster, proper diagnosis and treatment of the various diseases. These research contributions are expected to be useful for the design and development of software tools to support biologists and clinicians in their analysis procedures and for implementing the same in automated diagnostic systems. The aspectsof bacterial cell growth phase and cell division time determination is useful for automatic drug susceptibility tests conducted during drug design for effective control of disease caused by the bacteria.
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