3D Riesz-wavelet based Covariance descriptors for texture classification of lung nodule tissue in CT

Müller, Henning (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Cirujeda, Pol (Universitat Pompeu Fabra, Spain) ; Rubin, Daniel (Stanford University School of Medicine, USA) ; Aguilera, Todd (Stanford University School of Medicine, USA) ; Loo Jr., Billy (Stanford University School of Medicine, USA) ; Diehn, Maximilian (Stanford University School of Medicine, USA) ; Binefa, Xavier (Universitat Pompeu Fabra, Spain) ; Depeursinge, Adrien (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis))

In this paper we present a novel technique for characterizing and classifying 3D textured volumes belonging to different lung tissue types in 3D CT images. We build a volume-based 3D descriptor, robust to changes of size, rigid spatial transformations and texture variability, thanks to the integration of Riesz-wavelet features within a Covariance-based descriptor formulation. 3D Riesz features characterize the morphology of tissue density due to their response to changes in intensity in CT images. These features are encoded in a Covariance-based descriptor formulation: this provides a compact and flexible representation thanks to the use of feature variations rather than dense features themselves and adds robustness to spatial changes. Furthermore, the particular symmetric definite positive matrix form of these descriptors causes them to lay in a Riemannian manifold. Thus, descriptors can be compared with analytical measures, and accurate techniques from machine learning and clustering can be adapted to their spatial domain. Additionally we present a classification model following a “Bag of Covariance Descriptors” paradigm in order to distinguish three different nodule tissue types in CT: solid, ground-glass opacity, and healthy lung. The method is evaluated on top of an acquired dataset of 95 patients with manually delineated ground truth by radiation oncology specialists in 3D, and quantitative sensitivity and specificity values are presented.


Type de conférence:
full paper
Faculté:
Economie et Services
Ecole:
HEG VS HES-SO Valais-Wallis - Haute Ecole de Gestion & Tourisme
Institut:
Institut Informatique de gestion
Classification:
Informatique
Adresse bibliogr.:
Milan, Italy, 25-29 August 2015
Date:
Milan, Italy
25-29 August 2015
2015
Pagination:
4 p.
Titre du document hôte:
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2015
DOI:
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Note  Le statut de ce document est: non diffusé

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 Notice créée le 2015-11-16, modifiée le 2018-07-09

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