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Histo-fetch -- On-the-fly processing of gigapixel whole slide images simplifies and speeds neural network training
- Source :
- Journal of Pathology Informatics, Vol 13, Iss 1, Pp 7-7 (2022), Journal of Pathology Informatics
- Publication Year :
- 2021
-
Abstract
- We created a custom pipeline (histo-fetch) to efficiently extract random patches and labels from pathology whole slide images (WSIs) for input to a neural network on-the-fly. We prefetch these patches as needed during network training, avoiding the need for WSI preparation such as chopping/tiling. We demonstrate the utility of this pipeline to perform artificial stain transfer and image generation using the popular networks CycleGAN and ProGAN, respectively.<br />5 pages, 2 figures
- Subjects :
- FOS: Computer and information sciences
tensorflow
whole slide images
Computer Science - Artificial Intelligence
Image and Video Processing (eess.IV)
generative adversarial network
Computer applications to medicine. Medical informatics
R858-859.7
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
convolutional neural network
Health Informatics
02 engineering and technology
Electrical Engineering and Systems Science - Image and Video Processing
030218 nuclear medicine & medical imaging
Computer Science Applications
Pathology and Forensic Medicine
03 medical and health sciences
Artificial Intelligence (cs.AI)
0302 clinical medicine
FOS: Electrical engineering, electronic engineering, information engineering
0202 electrical engineering, electronic engineering, information engineering
Technical Note
Pathology
RB1-214
020201 artificial intelligence & image processing
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Journal of Pathology Informatics, Vol 13, Iss 1, Pp 7-7 (2022), Journal of Pathology Informatics
- Accession number :
- edsair.doi.dedup.....746f22df772f8bd7941e788e110d536c