Author: Krömer, P.; Nowaková, J.
Title: Medical Image Analysis with NVIDIA Jetson GPU Modules Cord-id: pks09y91 Document date: 2022_1_1
ID: pks09y91
Snippet: Medical imaging and image analysis are important elements of modern diagnostic and treatment methods. Intelligent image processing, pattern recognition, and data analysis can be leveraged to introduce a new level of detection, segmentation, and, in general, understanding to medical image analysis. However, modern image analysis methods such as deep neural networks are often connected with significant computational complexity, slowing their adoption. Recent embedded systems such as the NVIDIA Jet
Document: Medical imaging and image analysis are important elements of modern diagnostic and treatment methods. Intelligent image processing, pattern recognition, and data analysis can be leveraged to introduce a new level of detection, segmentation, and, in general, understanding to medical image analysis. However, modern image analysis methods such as deep neural networks are often connected with significant computational complexity, slowing their adoption. Recent embedded systems such as the NVIDIA Jetson general-purpose GPUs became a viable platform for efficient execution of some computational models. This work analyzes the performance and time and energy costs of several neural models for medical image analysis on different kinds of NVIDIA Jetson modules. The experiments are performed with the lung X-ray medical images in connection with the COVID-19 disease. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Search related documents:
Co phrase search for related documents- Try single phrases listed below for: 1
Co phrase search for related documents, hyperlinks ordered by date