Aniko T. Valko Keymodule Ltd.

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Recent developments in the CLiDE tool for extraction of chemical structure data from patents and other documents Aniko T. Valko Keymodule Ltd. Peter Johnson Vilmos A. Valko

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Recent developments in the CLiDE tool for extraction of chemical structure data from patents and other documents. Aniko T. Valko Keymodule Ltd. Peter Johnson Vilmos A. Valko. About CLiDE What is CLiDE for?. Summary. Performance against a benchmark set of images - PowerPoint PPT Presentation

Transcript of Aniko T. Valko Keymodule Ltd.

Page 1: Aniko  T.  Valko Keymodule  Ltd.

Recent developments in the CLiDE tool for extraction of

chemical structure data from patents and other documents

Aniko T. ValkoKeymodule Ltd.

Peter Johnson Vilmos A. Valko

Page 2: Aniko  T.  Valko Keymodule  Ltd.

Summary

1) About CLiDEWhat is CLiDE for?

2) Performance against a benchmark set of imagesAbout the benchmark setPerformance of CLiDEEnhancements made in CLiDEComparison with selected systems

3) Performance against selected patentsAbout patentsPerformance of CLiDEComparison with selected systems

4) Conclusions and future work

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Part 1:

About CLiDE

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What is CLiDE for?CLiDE is an Optical Chemical Structure Recognition (OCSR) software application, aimed at converting structure diagrams to computer-readable structures (i.e. connection tables)

PDF, DOC, DOCX, HTML

BMP, GIF, JPEG, PBM,PGM, PNG, PNM,

PPM, TIFF, XBM, XPM

Molfile, RGfile, SDfileCDX, CML, MRV

XML

Valence-violated atomNon-interpreted atomClashing atoms

Small bond angleAtoms at which CLiDE brokeup the structure

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Part 2:

Performance againsta benchmark set of images

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Benchmark set● Images of isolated structures, one structure per image

● #images: 5735

● US Patent Office Complex Work Unit

US07321045-20080122-C00150 US07320974-20080122-C00070US07323286-20080129-C00108 US07317070-20080108-C00008US07316739-20080108-C00281 US07314700-20080101-C00001US07320972-20080122-C00016 US07314876-20080101-C00035US07314576-20080101-C00035 US07314511-20080101-C00002

● Available on the OSRA web site

● Verification set: Each image is associated with a Molfile meant to describe

the correct connection table

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Test runs on the benchmark set● Test environment

CPU 3 Ghz Core 2 DuoMemory 4GBLinux distribution

Ubuntu 10.0.4 (64-bit)

● Test run per image1) CLiDE was run on an image2) CLiDE analysed the image and generated a connection

table3) The connection table extracted by CLiDE was compared (using canonical SMILES) to the corresponding connection table from the verification set (so called ‘ground truth’)● Performance measurements

1) Accuracy rate: the percentage of images that were correctly

processed by CLiDE2) Runtime: the total runtime measured over all the test runs

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Performance against benchmark set

3.2.0

4.2.0

4.4.0

5.0.0

5.2.0

5.2.1

5.4.0

5.5.0

5.5.1

5.5.2

5.5.3

5.5.4

0%10%20%30%40%50%60%70%80%90%

100%

00:00

07:12

14:24

21:36

28:48

36:00

43:12

50:24

57.62%

59.00%

58.91%

59.30%

59.30%

81.81%

82.75%

84.60%

85.78%

86.55%

87.79%

87.96%

Accuracy rate Runtime (min:sec)

Optimization andimprovements in CLiDE’s document segmentation method (see later)Auto correction of atom labelsBetter handling of aromatic ringsParsing chemical formulasAvoidance of loss of characters in atom labelsBetter handling of thick bondsFurther improvements to chemical formula parsing57.62% 87.98% 44 min 20 min

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Enhancements in CLiDECorrections in atom labels

59.30% 81.81%

● Auto correction of OCR errors in atom labels● Avoidance of misinterpretation of ‘Cl’ labels as Carbons

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Enhancements in CLiDEChemical formula parsing

82.75% 84.60%

● Parsing the chemical formula into a sub connection tableTwo-step process:

● Generating atom coordinates for the sub connection table

Super Atom Database: over 1000 super atoms, e.g. Me, Ph, Boc, TBDMS

Problem categories:● Super atoms in chemical formulas● Left- and right-aligned chemical formulas● Branching in chemical formulas● Chemical formulas with multiple attachments

● Chemical formulas with multiple attachments (―OCH2CH2O―)

● Super atoms in chemical formulas (―CO2Ph)● Left- and right-aligned chemical formulas (―CH2NH2 vs

NH2CH2 ―)● Branching in chemical formulas (―OC(CH3)3)

Future work:● Variables in chemical formulas (―CO2R, ―NHZ, ―SiR3)

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Enhancements in CLiDEAvoidance of loss of characters from atom labels

84.60% 85.78%

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Enhancements in CLiDEBetter handling of thick bonds (stereo indicators)

85.78% 86.55%

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Comparison with selected systems

0%10%20%30%40%50%60%70%80%90%

100%

74.48%70.27%

68.68%

68.68%

0.432

0.6128

OSRA Imago

Accuracy rate

57.62%

87.96%

Runtime (hour:min)

OSRA 1.3.6

OSRA 1.3.8

OSRA 1.3.9

OSRA 1.4.0

Imago 1.0

Imago 2.0

beta

0:00

1:12

2:24

3:36

4:48

6:00

7:12

05:51

04:50

04:50

04:54

00:15

01:52

OSRA Imago

CLiD

E

CLiD

E

00:44

00:20

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Is the benchmark set correct?

Verification set #Molfiles to be corrected: 117

US07314693-20080101-C00370.TIF US07314693-20080101-C00370.MOL

● Anomalies: 10● Stereo bonds: 22

US07316472-20080108-C00239.TIF US07316472-20080108-C00239.MOL

US07314872-20080101-C00024.TIF US07314872-20080101-C00024.MOL

● Incorrect sub connection tables for chemical formulae

(e.g. NC, H3CO2S, OCF3): 63● Errors in atom label: 14● Other kinds of error: 17

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Is the benchmark set correct?

Input images #images to be excluded: 16

● incorrect chemical formula: 1

US07314693-20080101-C00112.TIF

● disconnected atom: 1● incorrect or ambiguous

stereo bond: 6

US07314874-20080101-C00551.TIFUSRE039991-20080101-C00187.TIF USRE039991-20080101-C00188.TIF

● arrow with unknown meaning: 8

US07320974-20080122-C00022.TIF

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Performance after corrections

CLiDE 5.5.4 87.96% 90.11%

● #images: 5735● #corrected Molfiles: 117● #excluded images: 16

OSRA 1.4.0 68.68% 69.84%

Imago 2.0 beta 61.28% 61.91%

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Part 3:

Performance againstselected patents

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About patents

Patents# non-

Markush structures

US6410540 218

WO2008099019 668

Challenges:● Chemical structure diagrams

have to be identified within the document page

● Interpretation of Markush structures

Markush structures were excluded from our tests

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Challenge: Document segmentation

Page 65 of US6410540Underlined text

5.5.44.4.0

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Challenge: Document segmentation

Page 188 of WO2008019099Table

5.5.44.4.0

Performancemeasurements

● Accuracy rate

● Runtime● #Garbage structures:

The number of structures that were assigned tonon-chemical structure diagrams

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Performance of CLiDE

4.4.0 5.5.480%85%90%95%

100%88.90%

87.15%

Accuracy rate

US6410540

4.4.0 5.5.400:0000:0700:1400:2100:28

00:22

00:06

Runtime (hour:min)

4.4.0 5.5.40

100

200 14581

#Garbage structures

WO2008019099

4.4.0 5.5.40%

40%

80% 57.63%74.25%

Accuracy rate

4.4.0 5.5.400:0000:2800:5701:2601:55 01:34

00:04

Runtime (hour:min)

4.4.0 5.5.40

50010001500 1225

29

#Garbage structures

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Comparison with selected systemsComparison with OSRA

CLiDE OSRA60%70%80%90%

100%87.15%

70.18%

Accuracy rate

US6410540

CLiDE OSRA00:0000:0200:0500:0800:11

00:0600:09

Runtime (hour:min)

CLiDE OSRA0

50

100 81

29

#Garbage structures

WO2008019099

CLiDE OSRA40%

60%

80% 74.25%

51.64%

Accuracy rate

CLiDE OSRA00:00

00:28

00:57

00:04

00:58

Runtime (hour:min)

CLiDE OSRA0

100

200

29

183

#Garbage structures

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Part 4:

Conclusions and future work

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Conclusions● There has been considerable progress in OCSR, but nevertheless

there still remain many problems to be solved

● The test sets showcased the diversity and the frequency of the problem types

● Regarding performance:• CLiDE has greatly improved during the last few years• CLiDE compares well with the other OCSR systems available to

us for testing

● In favourable cases, OCSR as exemplified by CLiDE now approaches OCR in accuracy (90%)

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Future work

● Further improvements to structure recognition

● Filtering out garbage structures

● Identification and exclusion of non-chemical structure diagrams

● Further improvements to document segmentation

Short-term goals:

Long-term goals:● Contextual document analysis, aimed at linking

structures to text data

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Flavours of CLiDE

CLiDE is released in three variants, designed for individual user needs

CLiDE Standard

CLiDE Professional

CLiDE Batch

Designed for the individual chemist who wishes to convert selected images into editable structures for use in reports etc.

GUI enterprise version to process whole documents with interactive editing

Unsupervised extraction for database creation etc.

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Further information

www.keymodule.co.uk

[email protected]

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Acknowledgment

Peter Johnson Keymodule Ltd. and University of Leeds

Anthony P. Cook University of Leeds

Vilmos A. Valko Keymodule Ltd.

Reseller agents• SimBioSys Inc. (North America)• NeoTrident Technology Ltd.

(China)• Hulinks Inc. (Japan)

All users who gave us constructive feedback

Thank you for your attention