DEEP LEARNING IMAGE ANALYSIS WITH INCREASED MODULARITY AND REDUCED FOOTPRINT

DEEP LEARNING IMAGE ANALYSIS WITH INCREASED MODULARITY AND REDUCED FOOTPRINT

Systems/techniques that facilitate deep learning image analysis with increased modularity and reduced footprint are provided. In various embodiments, a system can access medical imaging data. In various aspects, the system can perform, via execution of a deep learning neural network, a plurality of...

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Bibliographische Detailangaben
Hauptverfasser: Cziria, Balázs Péter, Avinash, Gopal Biligeri, Rusko, Laszlo, Tan, Tao, Ferenczi, Lehel Mihály, Yang, Hongxu, Dong, Xiaomeng, Soni, Ravi, Tegzes, Pál
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Zusammenfassung:Systems/techniques that facilitate deep learning image analysis with increased modularity and reduced footprint are provided. In various embodiments, a system can access medical imaging data. In various aspects, the system can perform, via execution of a deep learning neural network, a plurality of inferencing tasks on the medical imaging data. In various instances, the deep learning neural network can comprise a common backbone in parallel with a plurality of task-specific backbones. In various cases, the plurality of task-specific backbones can respectively correspond to the plurality of inferencing tasks.