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Munich, Germany

Definiens Ag

USPTO Granted Patents = 45

% Expired Patents = 24.4

EPO Patents = 6

Forward Citations = 346

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38 inventors (with patents filed for the assignee):

Gerd K Binnig (27 out of 83 patents)

Guenter Schmidt (24 out of 31 patents)

Maria Athelogou (16 out of 16 patents)

4. Ralf Schoenmeyer (9 out of 9 patents)

5. Arno Schaepe (7 out of 7 patents)

6. Nicolas Brieu (6 out of 11 patents)

7. Günter Schmidt (6 out of 7 patents)

8. Martin Baatz (5 out of 5 patents)

9. Nathalie Harder (3 out of 3 patents)

10. Peter Ellenberg (3 out of 3 patents)

11. Ursula Benz (3 out of 3 patents)

12. Tamara Manuelian (3 out of 3 patents)

13. Joachim Diebold (3 out of 3 patents)

14. Michael R Alvers (3 out of 4 patents)

15. Peter Eschenbacher (3 out of 3 patents)

Core Competencies:

Cancer Recurrence Prediction

Pixelwise Descriptors

Image Segmentation

Tissue Grading

Biomarker Evaluation

Co-registered Images

Image-based Diagnostics

Semantic Images

Fluorescence Quantification

Anatomical Model Generation

45 patents: Sort by Forward Citations

1. 10579935 - System for predicting the recurrence of cancer in a cancer patient (2020-03-03),

2. 10474874 - Applying pixelwise descriptors to a target image that are generated by segmenting objects in other images (2019-11-12),

3. 10445557 - Learning pixel visual context from object characteristics to generate rich semantic images (2019-10-15),

4. 10438096 - Identifying and excluding blurred areas of images of stained tissue to improve cancer scoring (2019-10-08),

5. 10380491 - System for predicting the recurrence of cancer in a cancer patient (2019-08-13),

6. 10262189 - Evaluation of co-registered images of differently stained tissue slices (2019-04-16),

7. 9990713 - Detecting and visualizing correlations between measured correlation values and correlation reference values of a pathway (2018-06-05),

8. 9805248 - Applying pixelwise descriptors to a target image that are generated by segmenting objects in other images (2017-10-31),

9. 9779499 - Grading of glandular tissue cancer by detailed image analysis of stained tissue slices (2017-10-03),

10. 9741112 - Generating image-based diagnostic tests by optimizing image analysis and data mining of co-registered images (2017-08-22),

11. 9740957 - Learning pixel visual context from object characteristics to generate rich semantic images (2017-08-22),

12. 9740912 - Evaluation of co-registered images of differently stained tissue slices (2017-08-22),

13. 9466103 - Biomarker evaluation through image analysis (2016-10-11),

14. 9245337 - Context driven image mining to generate image-based biomarkers (2016-01-26),

15. 9177378 - Updating landmarks to improve coregistration as regions of interest are corrected (2015-11-03),

Company Overview

Definiens AG, based in Munich, specializes in advanced image analysis technologies aimed at enhancing cancer diagnostics and treatment. The company focuses on cancer recurrence prediction and biomarker evaluation, utilizing innovative methods such as semantic image generation and hyperspectral image analysis. Their expertise extends to co-registered images and fluorescence in situ hybridization, providing critical insights for tissue slice grading. Definiens is dedicated to improving clinical outcomes through precise and reliable image-based assessments.

Profile summary synthesized from public USPTO records and patent filings.

Company Badge

USPTO Data Jan 1 1976 - Oct 13 2026

45 Patents

#81 in W-8000 Munich

#1,166 in Germany

#15,436 in the World

Munich, Germany

Definiens Ag

Forward Citations = 346

38 inventors:

Gerd K Binnig (27 out of 83 patents)

Guenter Schmidt (24 out of 31 patents)

Maria Athelogou (16 out of 16 patents)

4. Ralf Schoenmeyer (9 out of 9 patents)

5. Arno Schaepe (7 out of 7 patents)

IDiyas Innovation Intelligence. (2026). Company Patent Portfolio: Definiens Ag. Retrieved from https://idiyas.com/company/definiens-ag

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]

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