Medical Image Analysis with NVIDIA Jetson GPU Modules
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F22%3A10249012" target="_blank" >RIV/61989100:27240/22:10249012 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-84910-8_25" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-84910-8_25</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-84910-8_25" target="_blank" >10.1007/978-3-030-84910-8_25</a>
Alternative languages
Result language
angličtina
Original language name
Medical Image Analysis with NVIDIA Jetson GPU Modules
Original language description
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. (C) 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF17_049%2F0008425" target="_blank" >EF17_049/0008425: A Research Platform focused on Industry 4.0 and Robotics in Ostrava Agglomeration</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Networks and Systems. Volume 312
ISBN
978-3-030-84909-2
ISSN
2367-3370
e-ISSN
2367-3389
Number of pages
10
Pages from-to
233-242
Publisher name
Springer
Place of publication
Cham
Event location
Tchaj-čung
Event date
Sep 1, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000704003000025