Title :

Malignant pleural mesothelioma segmentation for photodynamic therapy planning

Author(s) :

Brahim, Wael [Auteur]
Mestiri, Makram [Auteur]
Betrouni, Nacim [Auteur]
Troubles cognitifs dégénératifs et vasculaires - U 1171 [TCDV]
Troubles cognitifs dégénératifs et vasculaires - U1171
Hamrouni, Kamel [Auteur]

Journal title :

Computerized medical imaging and graphics . the official journal of the Computerized Medical Imaging Society

Abbreviated title :

Comput Med Imaging Graph

Publication date :

2017-07-26

ISSN :

1879-0771

English keyword(s) :

Malignant pleural mesothelioma
Mesothelioma texture analysis
Thoracic cavity segmentation
Photodynamic therapy
Computed tomography

HAL domain(s) :

Sciences du Vivant [q-bio]

English abstract : [en]

Medical imaging modalities such as computed tomography (CT) combined with computer-aided diagnostic processing have already become important part of clinical routine specially for pleural diseases. The segmentation of the ...
Show more >Medical imaging modalities such as computed tomography (CT) combined with computer-aided diagnostic processing have already become important part of clinical routine specially for pleural diseases. The segmentation of the thoracic cavity represents an extremely important task in medical imaging for different reasons. Multiple features can be extracted by analyzing the thoracic cavity space and these features are signs of pleural diseases including the malignant pleural mesothelioma (MPM) which is the main focus of our research. This paper presents a method that detects the MPM in the thoracic cavity and plans the photodynamic therapy in the preoperative phase. This is achieved by using a texture analysis of the MPM region combined with a thoracic cavity segmentation method. The algorithm to segment the thoracic cavity consists of multiple stages. First, the rib cage structure is segmented using various image processing techniques. We used the segmented rib cage to detect feature points which represent the thoracic cavity boundaries. Next, the proposed method segments the structures of the inner thoracic cage and fits 2D closed curves to the detected pleural cavity features in each slice. The missing bone structures are interpolated using a prior knowledge from manual segmentation performed by an expert. Next, the tumor region is segmented inside the thoracic cavity using a texture analysis approach. Finally, the contact surface between the tumor region and the thoracic cavity curves is reconstructed in order to plan the photodynamic therapy. Using the adjusted output of the thoracic cavity segmentation method and the MPM segmentation method, we evaluated the contact surface generated from these two steps by comparing it to the ground truth. For this evaluation, we used 10 CT scans with pathologically confirmed MPM at stages 1 and 2. We obtained a high similarity rate between the manually planned surface and our proposed method. The average value of Jaccard index was about 0.79 and we obtained a value of 0.88 using the Dice index.Show less >

Language :

Anglais

Audience :

Internationale

Popular science :

Non

Administrative institution(s) :

CHU Lille
CNRS
Inserm
Université de Lille

Collections :

• Lille Neurosciences & Cognition (LilNCog) - U 1172

Research team(s) :

Troubles cognitifs dégénératifs et vasculaires

Submission date :

2019-11-27T13:02:18Z