(S(Semiemi-) A-) Automaticutomatic RRecognitionecognition ofof MMicroorganismsicroorganisms inin W Waterater

K. Rodenacker, P. Gais2, U. Jütting and B. A. HenseGSF-IBB, 2GSF-Patho, Neuherberg, Germany

Karsten Rodenacker GSF-IBB AG2 2

ContentContent Introduction Material Methods Results Summary and Discussion

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IntroductionIntroduction Studies on the

effects of toxicants on the biocenosis of aquatic model ecosystem Characterization of

plankton commun.(identification, counting of phyto-plankton)

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MaterialMaterial Preparation

Container of semi-permeable LDPE tubes containing the test substance

Water column

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MaterialMaterial Data gathering

Sedimentation Slide preparation Microscopy

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MaterialMaterial Data processing

with QWin, QUIPS Scan path and

autofocus Digitization and

storage~45 sec/image

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MaterialMaterial Some organisms to

be classified

GYLA PEUM MIPU CRER

HUKU OOMA CHAC CRMA

QULA KICO ZIGA ACMX

CLSA PLGE ZIGA

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MethodsMethods Data processing

with IDL Image segmentation Feature extraction Classification Re-classification

and training

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MethodsMethods Image

segmentation:(two-step method) Rough

segmentationimage threshold

Fine segmentationobject threshold(RATS)

Unbiased count(forbidden line)

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MethodsMethods Feature extraction

Shape geometrical analytical (Fourier,

curvature) topological (convex

hull, distance map) algebraic (moments,

PCA)

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MethodsMethods Feature extraction

Extinction(optical density)

histogram featuresmean (M1), SD (M2), skewness (M3) etc.

moments (algebraic)

transmitted light optical density

Histogram of values of transmitted light

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MethodsMethods Classification

Hierarchical tree classifier based on stepwise linear discriminance analysis

ALL

GYLA

KICO

OOMA

CLSA

CHAC

CRER

PEUM

Artefacts

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MethodsMethods Re-Classification

Interaction Control Correction Training

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Preliminary ResultsPreliminary Results Comparison of

manual and automatic procedure

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Summary and Summary and DiscussionDiscussion

Difficulties or failures Separate softwares

(Qwin, IDL) Autofocus

automized microscope

Segmentation Unlimited number of

organism groups

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Summary and Summary and DiscussionDiscussion

Successes Effective training

system for biologists AND computer scientists

Very good collaboration between the different faculties

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Summary and Summary and DiscussionDiscussion

Outlook Fluorescence Multiple focal depth Type specific object

shape features (dominant feature points)

Texture object features