Cerebral Microbleed Detection Via Fourier Descriptor with Dual Domain Distribution Modeling

Hangfan Liu, Tanweer Rashid, Mohamad Habes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this study we propose a novel cerebral microbleed (CMB) detection technique which simultaneously utilizes distribution information in dual domains and shape information obtained by a Fourier descriptor, and does not rely on a large set of training data. Specifically, the dual domain distribution modeling aims to simultaneously examine the image content in both gradient domain and voxel domain, while the Fourier descriptor further characterize the shape of the candidate region. A set of labeled data is used to form the dualdomain distribution as well as the distribution of Fourier coefficients. Then the probability of a region containing a CMB is estimated by combining the two types of distributions. Experimental results show that the proposed approach is efficient and desirable for scenarios where the number of samples is limited.

Original languageEnglish (US)
Title of host publicationISBI Workshops 2020 - International Symposium on Biomedical Imaging Workshops, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728174013
DOIs
StatePublished - Apr 2020
Event17th IEEE International Symposium on Biomedical Imaging Workshops, ISBI Workshops 2020 - Iowa City, United States
Duration: Apr 4 2020 → …

Publication series

NameISBI Workshops 2020 - International Symposium on Biomedical Imaging Workshops, Proceedings

Conference

Conference17th IEEE International Symposium on Biomedical Imaging Workshops, ISBI Workshops 2020
CountryUnited States
CityIowa City
Period4/4/20 → …

Keywords

  • Cerebral Microbleed Detection.
  • Dual Domain Distribution
  • Fourier Descriptor

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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