View source for 17932311. MEDICAL IMAGING DATA NORMALIZATION FOR ANIMAL STUDIES simplified abstract (Siemens Healthcare GmbH)

=MEDICAL IMAGING DATA NORMALIZATION FOR ANIMAL STUDIES=


==Organization Name==

[[:Category:Siemens Healthcare GmbH|Siemens Healthcare GmbH]]


[[Category:Siemens Healthcare GmbH]]

==Inventor(s)==

[[:Category:Bernhard Geiger of Cranbury NJ (US)|Bernhard Geiger of Cranbury NJ (US)]][[Category:Bernhard Geiger of Cranbury NJ (US)]]

==MEDICAL IMAGING DATA NORMALIZATION FOR ANIMAL STUDIES - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17932311 titled 'MEDICAL IMAGING DATA NORMALIZATION FOR ANIMAL STUDIES

==Simplified Explanation==

The abstract describes a system and method for normalizing medical imaging data across different species and breeds of animals to enable the use of machine trained models across various subjects.

* Image data of non-human subjects is acquired.
* The data is registered using a standardized model.
* Segmentation is performed using a machine trained model.

== Potential Applications ==
This technology could be applied in veterinary medicine, wildlife conservation, and biomedical research.

== Problems Solved ==
This innovation addresses the challenge of using machine trained models across different species and breeds of animals in medical imaging.

== Benefits ==
The technology allows for more efficient and accurate analysis of medical imaging data in a variety of animal subjects.

== Potential Commercial Applications ==
Potential commercial applications include software development for veterinary clinics, research institutions, and wildlife organizations.

== Possible Prior Art ==
Prior art may include research on image normalization techniques in medical imaging and machine learning applications in veterinary medicine.

=== Unanswered Questions ===

== How does this technology handle variations in anatomy between different species and breeds of animals? ==
The system likely incorporates algorithms to account for anatomical differences and adjust the normalization process accordingly.

== What are the limitations of using machine trained models across different species and breeds of animals in medical imaging? ==
The technology may face challenges in accurately segmenting images with significant anatomical variations or limited training data for certain species.


==Original Abstract Submitted==

Systems and methods that normalize medical imaging data between different species and breeds of animals in order to allow for cross-species and crossbreed usage of machine trained models. Image data of a non-human subject is acquired, registered using a standardized model, and segmented using a machine trained model.



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