Automatic bone and marrow extraction from dual energy ct through svm margin-based multi-material decomposition model selection Conference Paper

  


Authors: Veeraraghavan, H.; Fehr, D.; Schmidtlein, R.; Hwang, S.; Deasy, J. O.
Title: Automatic bone and marrow extraction from dual energy ct through svm margin-based multi-material decomposition model selection
Conference Title: 5th MLMI 2014 International Workshop held in conjunction with MICCAI 2014
Abstract: In this work, we present a fully-automatic approach for segmenting bone and marrow structures from dual energy CT (DECT) images. The images are represented using a multi-material decomposition model (MMD) computed from a triplet of physical materials at two different energy attenuation levels. We employ support vector machine learning to select the most relevant MMD model for the anatomical structure of interest so that highly accurate segmentation of the said structures can be achieved. We evaluated our approach for segmenting bone and marrow structures with varying amounts of metastatic bone disease on multiple longitudinal follow up patient scans. Our approach shows consistent and robust segmentation despite changes in bone density due to disease progression, high-density contrast material uptake in neighboring tissue, and significant metal artifacts.
Keywords: computerized tomography; disease progression; artificial intelligence; bone; image segmentation; anatomical structures; learning systems; automatic approaches; contrast material; energy attenuation; highly accurate; metal artifacts; robust segmentation
Journal Title Lecture Notes in Computer Science
Volume: 8679
Conference Dates: 2014 Sep 14
Conference Location: Boston, MA
ISBN: 0302-9743
Publisher: Springer  
Date Published: 2014-01-01
Start Page: 149
End Page: 156
Language: English
PROVIDER: scopus
DOI: 10.1007/978-3-319-10581-9_19
DOI/URL:

http://www.scopus.com/inward/record.url?eid=2-s2.0-84921789142&partnerID=40&md5=cbd9df6ffe4340007039b07880f39ed5
Notes: Chapter in "Machine Learning in Medical Imaging" (ISBN: 978-3-319-10580-2) -- Export Date: 2 March 2015 -- Source: Scopus
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MSK Authors
  1. Sinchun Hwang
    96 Hwang
  2. Charles Ross Schmidtlein
    107 Schmidtlein
  3. Joseph Owen Deasy
    524 Deasy
  4. Harini Veeraraghavan
    159 Veeraraghavan
  5. Duc Alexandre Fehr
    7 Fehr
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