Bayesian Feature Pyramid Networks for Automatic Multi-Label Segmentation of Chest X-rays and Assessment of Cardio-Thoratic Ratio

Roman Solovyev, Iaroslav Melekhov, Timo Lesonen, Elias Vaattovaara, Osmo Tervonen, Aleksei Tiulpin

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

7 Sitaatiot (Scopus)

Abstrakti

Cardiothoratic ratio (CTR) estimated from chest radiographs is a marker indicative of cardiomegaly, the presence of which is in the criteria for heart failure diagnosis. Existing methods for automatic assessment of CTR are driven by Deep Learning-based segmentation. However, these techniques produce only point estimates of CTR but clinical decision making typically assumes the uncertainty. In this paper, we propose a novel method for chest X-ray segmentation and CTR assessment in an automatic manner. In contrast to the previous art, we, for the first time, propose to estimate CTR with uncertainty bounds. Our method is based on Deep Convolutional Neural Network with Feature Pyramid Network (FPN) decoder. We propose two modifications of FPN: replace the batch normalization with instance normalization and inject the dropout which allows to obtain the Monte-Carlo estimates of the segmentation maps at test time. Finally, using the predicted segmentation mask samples, we estimate CTR with uncertainty. In our experiments we demonstrate that the proposed method generalizes well to three different test sets. Finally, we make the annotations produced by two radiologists for all our datasets publicly available.

AlkuperäiskieliEnglanti
OtsikkoAdvanced Concepts for Intelligent Vision Systems - 20th International Conference, ACIVS 2020, Proceedings
ToimittajatJacques Blanc-Talon, Patrice Delmas, Wilfried Philips, Dan Popescu, Paul Scheunders
Sivut117-130
Sivumäärä14
ISBN (elektroninen)978-3-030-40605-9
DOI - pysyväislinkit
TilaJulkaistu - helmik. 2020
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaInternational Conference on Advanced Concepts for Intelligent Vision Systems - Auckland, Uusi-Seelanti
Kesto: 10 helmik. 202014 helmik. 2020
Konferenssinumero: 20

Julkaisusarja

NimiLecture Notes in Computer Science
KustantajaSpringer
Vuosikerta12002

Conference

ConferenceInternational Conference on Advanced Concepts for Intelligent Vision Systems
LyhennettäACIVS
Maa/AlueUusi-Seelanti
KaupunkiAuckland
Ajanjakso10/02/202014/02/2020

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