Tumor delineation for brain radiosurgery by a ConvNet and non-uniform patch generation

Egor Krivov, Valery Kostjuchenko, Alexandra Dalechina, Boris Shirokikh, Gleb Makarchuk, Alexander Denisenko, Andrey Golanov, Mikhail Belyaev

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

    4 Citations (Scopus)

    Abstract

    Deep learning methods are actively used for brain lesion segmentation. One of the most popular models is DeepMedic, which was developed for segmentation of relatively large lesions like glioma and ischemic stroke. In our work, we consider segmentation of brain tumors appropriate to stereotactic radiosurgery which limits typical lesion sizes. These differences in target volumes lead to a large number of false negatives (especially for small lesions) as well as to an increased number of false positives for DeepMedic. We propose a new patch-sampling procedure to increase network performance for small lesions. We used a 6-year dataset from a stereotactic radiosurgery center. To evaluate our approach, we conducted experiments with the three most frequent brain tumors: metastasis, meningioma, schwannoma. In addition to cross-validation, we estimated quality on a hold-out test set which was collected several years later than the train one. The experimental results show solid improvements in both cases.

    Original languageEnglish
    Title of host publicationPatch-Based Techniques in Medical Imaging - 4th International Workshop, Patch-MI 2018, Held in Conjunction with MICCAI 2018, Proceedings
    EditorsBrent C. Munsell, Guorong Wu, Pierrick Coupé, Gerard Sanroma, Yiqiang Zhan, Wenjia Bai
    PublisherSpringer Verlag
    Pages122-129
    Number of pages8
    ISBN (Print)9783030004996
    DOIs
    Publication statusPublished - 2018
    Event4th International Workshop on Patch-Based Techniques in Medical Imaging, Patch-MI 2018 Held in Conjunction with 21st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018 - Granada, Spain
    Duration: 20 Sep 201820 Sep 2018

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume11075 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference4th International Workshop on Patch-Based Techniques in Medical Imaging, Patch-MI 2018 Held in Conjunction with 21st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018
    Country/TerritorySpain
    CityGranada
    Period20/09/1820/09/18

    Keywords

    • CNN
    • MRI
    • Segmentation
    • Stereotactic radiosurgery

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