TY - JOUR
T1 - On Edge Computing for Remote Pathology Consultations and Computations
AU - Sacco, Alessio
AU - Esposito, Flavio
AU - Marchetto, Guido
AU - Kolar, Grant
AU - Schwetye, Kate
N1 - Funding Information:
Manuscript received September 30, 2019; revised February 10, 2020 and June 11, 2020; accepted July 2, 2020. Date of publication July 7, 2020; date of current version September 3, 2020. This work is part of the AI@SLU initiative and has been partially supported by NSF under Award Numbers CNS1647084, CNS1836906, and CNS1908574. (Corresponding author: Alessio Sacco.) Alessio Sacco is with the Control and Computer Engineering of Po-litecnico di Torino, 10129 Torino, Italy, and also with the Department of Computer Science, Saint Louis University, Saint Louis, MO 63103 USA (e-mail: alessio_sacco@polito.it).
Publisher Copyright:
© 2013 IEEE.
PY - 2020/9
Y1 - 2020/9
N2 - Telepathology aims to replace the pathology operations performed on-site, but current systems are limited by their prohibitive cost, or by the adopted underlying technologies. In this work, we contribute to overcoming these limitations by bringing the recent advances of edge computing to reduce latency and increase local computation abilities to the pathology ecosystem. In particular, this paper presents LiveMicro, a system whose benefit is twofold: on one hand, it enables edge computing driven digital pathology computations, such as data-driven image processing on a live capture of the microscope. On the other hand, our system allows remote pathologists to diagnosis in collaboration in a single virtual microscope session, facilitating continuous medical education and remote consultation, crucial for under-served and remote hospital or private practice. Our results show the benefits and the principles underpinning our solution, with particular emphasis on how the pathologists interact with our application. Additionally, we developed simple yet effective diagnosis-aided algorithms to demonstrate the practicality of our approach.
AB - Telepathology aims to replace the pathology operations performed on-site, but current systems are limited by their prohibitive cost, or by the adopted underlying technologies. In this work, we contribute to overcoming these limitations by bringing the recent advances of edge computing to reduce latency and increase local computation abilities to the pathology ecosystem. In particular, this paper presents LiveMicro, a system whose benefit is twofold: on one hand, it enables edge computing driven digital pathology computations, such as data-driven image processing on a live capture of the microscope. On the other hand, our system allows remote pathologists to diagnosis in collaboration in a single virtual microscope session, facilitating continuous medical education and remote consultation, crucial for under-served and remote hospital or private practice. Our results show the benefits and the principles underpinning our solution, with particular emphasis on how the pathologists interact with our application. Additionally, we developed simple yet effective diagnosis-aided algorithms to demonstrate the practicality of our approach.
KW - Telepathology
KW - collaborative pathology
KW - edge computing
UR - http://www.scopus.com/inward/record.url?scp=85090491172&partnerID=8YFLogxK
U2 - 10.1109/JBHI.2020.3007661
DO - 10.1109/JBHI.2020.3007661
M3 - Article
C2 - 32750953
AN - SCOPUS:85090491172
SN - 2168-2194
VL - 24
SP - 2523
EP - 2534
JO - IEEE Journal of Biomedical and Health Informatics
JF - IEEE Journal of Biomedical and Health Informatics
IS - 9
M1 - 9134906
ER -