Multi-target osteosarcoma MRI recognition with texture context features based on CRF

Wen Bo Huang, Dunwei Wen, Yang Yan, Man Yuan, Ke Wang

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

    12 Citations (Scopus)

    Abstract

    In the recognition of osteosarcoma magnetic resonance images (MRI), the probability of a pixel belonging to a class is not only related to its own features, but also closely correlated with the information distribution of the surrounding pixels. However, it is currently unable to recognize the osteosarcoma lesions and surrounding issues simultaneously. In order to solve the problem, we propose a fully automated approach to osteosarcoma MRI segmentation and recognition. It uses Conditional Random Field (CRF) model to incorporate multiple features, especially the texture context features, which are based on the relative position of pixels' texture and make a significant difference in more accurately determining which class a pixel belongs to. Further, we propose to model the mutual constraint relations between the targets (bone tumor, soft tissue, etc.) features in the osteosarcoma MRI, and train the tagging samples with the Joint-boost algorithm. Our experimental results show that the proposed method is effective and encouraging. It is especially superior for recognizing tumors with irregular shape and structure, which are identified with low accuracy in other methods.

    Original languageEnglish
    Title of host publication2016 International Joint Conference on Neural Networks, IJCNN 2016
    Pages3978-3983
    Number of pages6
    ISBN (Electronic)9781509006199
    DOIs
    Publication statusPublished - 31 Oct. 2016
    Event2016 International Joint Conference on Neural Networks, IJCNN 2016 - Vancouver, Canada
    Duration: 24 Jul. 201629 Jul. 2016

    Publication series

    NameProceedings of the International Joint Conference on Neural Networks
    Volume2016-October

    Conference

    Conference2016 International Joint Conference on Neural Networks, IJCNN 2016
    Country/TerritoryCanada
    CityVancouver
    Period24/07/1629/07/16

    Keywords

    • Conditional random fields
    • Multi-target recognition
    • Osteosarcoma MRI
    • Texture context features

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