Factors influencing the reliability of a CT angiographybased deep learning method for infarct volume estimation

Research output: Contribution to journal › Article › Scientific › peer-review

Original language	English
Article number	tzae001
Journal	British Journal of Radiology
Volume	6
Issue number	1
Number of pages	7
ISSN	0007-1285
DOIs	https://doi.org/10.1093/bjro/tzae001
Publication status	Published - 2024
MoE publication type	A1 Journal article-refereed

Fields of Science

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title = "Factors influencing the reliability of a CT angiographybased deep learning method for infarct volume estimation",

keywords = "3126 Surgery, anesthesiology, intensive care, radiology",

author = "Lasse Hokkinen and Teemu M{\"a}kel{\"a} and Sauli Savolainen and Marko Kangasniemi",

year = "2024",

doi = "10.1093/bjro/tzae001",

language = "English",

volume = "6",

journal = "British Journal of Radiology",

issn = "0007-1285",

publisher = "BRITISH INSTITUTE OF RADIOLOGY",

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T1 - Factors influencing the reliability of a CT angiographybased deep learning method for infarct volume estimation

AU - Hokkinen, Lasse

AU - Mäkelä, Teemu

AU - Savolainen, Sauli

AU - Kangasniemi, Marko

PY - 2024

Y1 - 2024

KW - 3126 Surgery, anesthesiology, intensive care, radiology

U2 - 10.1093/bjro/tzae001

DO - 10.1093/bjro/tzae001

M3 - Article

SN - 0007-1285

VL - 6

JO - British Journal of Radiology

JF - British Journal of Radiology

IS - 1

M1 - tzae001

ER -