17932311. MEDICAL IMAGING DATA NORMALIZATION FOR ANIMAL STUDIES simplified abstract (Siemens Healthcare GmbH)
Contents
- 1 MEDICAL IMAGING DATA NORMALIZATION FOR ANIMAL STUDIES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 MEDICAL IMAGING DATA NORMALIZATION FOR ANIMAL STUDIES - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 How does this technology handle variations in anatomy between different species and breeds of animals?
- 1.11 What are the limitations of using machine trained models across different species and breeds of animals in medical imaging?
- 1.12 Original Abstract Submitted
MEDICAL IMAGING DATA NORMALIZATION FOR ANIMAL STUDIES
Organization Name
Inventor(s)
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.