DAME (Deep learning Algorithms for Medical image Evaluation) (Q4301512): Difference between revisions
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Project Q4301512 in Germany, Netherlands | |||
Revision as of 20:51, 10 June 2022
Project Q4301512 in Germany, Netherlands
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | DAME (Deep learning Algorithms for Medical image Evaluation) |
Project Q4301512 in Germany, Netherlands |
Statements
593,128.0 Euro
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1,186,256.0 Euro
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50.0 percent
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1 October 2017
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1 October 2021
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Universitair Medisch Centrum Groningen (UMCG)
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Q3985026 (Deleted Item)
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53°9'13.36"N, 8°12'34.56"E
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51°50'40.67"N, 6°38'44.84"E
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52°9'4.36"N, 7°23'30.73"E
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53°13'24.67"N, 6°34'29.71"E
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53°13'9.77"N, 6°34'39.68"E
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53°13'11.28"N, 6°34'39.43"E
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The aim of this project is to explore software solutions using deep learning technology to achieve automatic, fast and reliable detection of abnormalities (such as cancer) in medical images. The main advantage of this innovation is the development of a generic algorithm to recognize patterns in images, independent of the type of image (CT, MR, etc) or type of abnormality. This allows to use the same software system to solve a multitude of different clinical problems. The goal is not only to quickly identify healthy individuals, but also to detect abnormalities that are not directly linked to the clinical question (incidental findings). By automatically identifying all abnormalities in the images, missing something crucial will be avoided. (English)
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