From local to global : a holistic lung graph model

Dicente Cid, Yashin (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) ; University of Geneva) ; Jiménez del Toro, Oscar Alfonso (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) ; University of Geneva ; University Hospitals of Geneva (HUG), Geneva, Switzerland) ; Platon, Alexandra (University Hospitals of Geneva (HUG), Geneva, Switzerland) ; Müller, Henning (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) ; University of Geneva) ; Poletti, Pierre-Alexandre (University Hospitals of Geneva (HUG), Geneva, Switzerland)

Lung image analysis is an essential part in the assessment of pulmonary diseases. Through visual inspection of CT scans, radiologists detect abnormal patterns in the lung parenchyma, aiming to establish a timely diagnosis and thus improving patient outcome. However, in a generalized disorder of the lungs, such as pulmonary hypertension, the changes in organ tissue can be elusive, requiring additional invasive studies to confirm the diagnosis. We present a graph model that quantifies lung texture in a holistic approach enhancing the analysis between pathologies with similar local changes. The approach extracts local state-of-the-art 3D texture descriptors from an automatically generated geometric parcellation of the lungs. The global texture distribution is encoded in a weighted graph that characterizes the correlations among neighboring organ regions. A data set of 125 patients with suspicion of having a pulmonary vascular pathology was used to evaluate our method. Three classes containing 47 pulmonary hypertension, 31 pulmonary embolism and 47 control cases were classified in a one vs. one setup. An area under the curve of up to 0.85 was obtained adding directionality to the edges of the graph architecture. The approach was able to identify diseased patients, and to distinguish pathologies with abnormal local and global blood perfusion defects.


Keywords:
Faculty:
Economie et Services
School:
HEG-VS
Institute:
Institut Informatique de gestion
Subject(s):
Informatique
Publisher:
Cham, Springer
Date:
2018-09
Cham
Springer
Pagination:
Pp. 786-793
Published in:
Medical image computing and computer assisted intervention – MICCAI 2018 : 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part II
Author of the book:
Frangi, Alejandro F. ; (ed.) ; University of Leeds, UK
DOI:
ISBN:
978-3-030-00933-5
External resources:
Appears in Collection:

Note: The status of this file is: restricted


 Record created 2018-11-14, last modified 2018-12-20

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