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NEMČEK, J. VIČAR, T. JAKUBÍČEK, R.
Originální název
Weakly Supervised Deep Learning-based Intracranial Hemorrhage Localization
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
Intracranial hemorrhage is a life-threatening disease, which requires fast medical intervention. Owing to the duration of data annotation, head CT images are usually available only with slice-level labeling. However, information about the exact position could be beneficial for a radiologist. This paper presents a fully automated weakly supervised method of precise hemorrhage localization in axial CT slices using only position-free labels. An algorithm based on multiple instance learning is introduced that generates hemorrhage likelihood maps for a given CT slice and even finds the coordinates of bleeding. Two different publicly available datasets are used to train and test the proposed method. The Dice coefficient, sensitivity and positive predictive value of 58.08 %, 54.72 % and 61.88 %. respectively, are achieved on data from the test dataset.
Klíčová slova
Intracranial Hemorrhage; Computed Tomography; Deep Learning; Convolutional Neural Network; Weakly Supervised Learning; Localization; Attention; Multiple Instance Learning
Autoři
NEMČEK, J.; VIČAR, T.; JAKUBÍČEK, R.
Vydáno
1. 3. 2022
Nakladatel
SciTePress
Místo
SETUBAL
ISBN
978-989-758-552-4
Kniha
Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - (Volume 2)
Strany od
111
Strany do
116
Strany počet
6
URL
https://www.scitepress.org/Link.aspx?doi=10.5220/0010825000003123
Plný text v Digitální knihovně
http://hdl.handle.net/11012/208176
BibTex
@inproceedings{BUT178071, author="Jakub {Nemček} and Tomáš {Vičar} and Roman {Jakubíček}", title="Weakly Supervised Deep Learning-based Intracranial Hemorrhage Localization", booktitle="Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - (Volume 2) ", year="2022", pages="111--116", publisher="SciTePress", address="SETUBAL", doi="10.5220/0010825000003123", isbn="978-989-758-552-4", url="https://www.scitepress.org/Link.aspx?doi=10.5220/0010825000003123" }