W-net for whole-body bone lesion detection on 68 ga-pentixafor PET/CT imaging of multiple myeloma patients

Lina Xu, Giles Tetteh, Mona Mustafa, Jana Lipkova, Yu Zhao, Marie Bieth, Patrick Christ, Marie Piraud, Bjoern Menze, Kuangyu Shi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

The assessment of bone lesion is crucial for the diagnostic and therapeutic planning of multiple myeloma (MM). 68 Ga-Pentixafor PET/CT can capture the abnormal molecular expression of CXCR-4 in addition to anatomical changes. However, the whole-body detection of dozens of lesions on hybrid imaging is tedious and error-prone. In this paper, we adopt a cascaded convolutional neural networks (CNN) to form a W-shaped architecture (W-Net). This deep learning method leverages multimodal information for lesion detection. The first part of W-Net extracts skeleton from CT scan and the second part detect and segment lesions. The network was tested on 12 68 Ga-Pentixafor PET/CT scans of MM patients using 3-folder cross validation. The preliminary results showed that W-Net can automatically learn features from multimodal imaging for MM bone lesion detection. The proof-of-concept study encouraged further development of deep learning approach for MM lesion detection with increased number of subjects.

Original languageEnglish
Title of host publicationMolecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment - 5th International Workshop, CMMI 2017 2nd International Workshop, RAMBO 2017 and 1st International Workshop, SWITCH 2017 Held in Conjunction with MICCAI 2017, Proceedings
EditorsM. Jorge Cardoso, Tal Arbel
PublisherSpringer Verlag
Pages23-30
Number of pages8
ISBN (Print)9783319675633
DOIs
StatePublished - 2017
Event5th International Workshop on Computational Methods for Molecular Imaging, CMMI 2017, 2nd International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2017 and 1st International Stroke Workshop on Imaging and Treatment Challenges, SWITCH 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017 - Quebec City, Canada
Duration: 14 Sep 201714 Sep 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10555 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Workshop on Computational Methods for Molecular Imaging, CMMI 2017, 2nd International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2017 and 1st International Stroke Workshop on Imaging and Treatment Challenges, SWITCH 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017
Country/TerritoryCanada
CityQuebec City
Period14/09/1714/09/17

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