INACIO, Eloïse; LAFITTE, Luc; SUTTER, Olivier; SEROR, Olivier; DENIS DE SENNEVILLE, Baudouin; POIGNARD, Clair

doi:10.1109/MELECON53508.2022.9842866

Métadonnées

Afficher la notice complète

Licence d’utilisation du document

INACIO, Eloïse
Modélisation Mathématique pour l'Oncologie [MONC]

LAFITTE, Luc
Modélisation Mathématique pour l'Oncologie [MONC]

SUTTER, Olivier
Hôpital Avicenne [AP-HP]

Langue

Communication dans un congrès

Ce document a été publié dans

IEEE - MELECON 2022 - 21st Mediterranean Electrotechnical Conference, 2022-06-14, Palerme.

Résumé en anglais

The objective of this paper is to provide a stepforward towards the per procedural visualisation of the electric field distribution during a clinical irreversible electroporation (IRE) procedure. To this end, an automated workflow is needed to compute the electric field distribution on a single Cone Beam Computed Tomography (CBCT) scan. The aim of the current paper is to propose a deep learning strategy for the automatic segmentation of the needles. In particular, a novel coarse-to-fine approach is proposed to extract relevant needle information from the CBCT scan, despite inherent artefacts generated during capture. The obtained needle information is subsequently fed into a standard static linear model for the electric field computation. Since the setup is performed in the medical image framework, the electric field distribution and the region of interest are visible to provide to the radiologist a visual evaluation of the treatment. The segmentation results are evaluated on 8 of the 16 patients of the dataset using the Dice coefficient to compare the predicted segmentation with the ground truth. The proposed segmentation method is fast (around 2 minutes are needed with a commodity hardware), allowing its use in a clinical setting.< Réduire

Mots clés en anglais

Deep Neural Network

Fine-object Segmentation

CBCT

Electric field distribution

Métadonnées

Partager cette publication !

Licence d’utilisation du document

Automated needle localisation for electric field computation during an electroporation ablation

Langue

Ce document a été publié dans

Résumé en anglais

Mots clés en anglais

URI

DOI

Origine

Unités de recherche