Towards large-scale MR thigh image analysis via an integrated quantification framework

Chaowei Tan, Kang Li, Zhennan Yan, Jingru Yi, Pengxiang Wu, Hui Jing Yu, Klaus Engelke, Dimitris N. Metaxas

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper, we focus on large scale magnetic resonance (MR) thigh image analysis via accurately quantifying major tissue composition in the thigh by a novel integrated framework. Specifically, the framework is able to distinguish muscular tissue and different types of adipose tissues, i.e. subcutaneous adipose tissue(SAT), inter- and intra-muscular adipose tissue (IMAT and IAMAT), efficiently. Deformable models and learning based techniques are integrated in the novel framework to enable robust quantification. Importantly, extensive evaluations are conducted on a large set of 3D MR thigh volumes from longitudinal studies of hundreds of subjects to investigate radiographic osteoarthritis (OA) related changes of muscular and adipose tissue volumes. The analysis is constructed by two subcohorts (G1 and G2). G2 has 61 patients which keep healthy at baseline (BL) and 48 months (M48), while G1's 85 patients are healthy at BL but have knee OA at M48. Paired t-tests are used to investigate the changes of these tissue size over time passing with/without pathological progression. The experimental results show that, in G1, patients’ IMAT and IAMAT are statistically significant respectively, yet G2 has no such variation in the same tissue type. Thus we conclude from the statistical analysis that age may not directly affect thigh tissues, but IMAT and IAMAT may have obvious changes in patients with knee OA.

Original languageEnglish (US)
Pages (from-to)63-76
Number of pages14
JournalNeurocomputing
Volume229
DOIs
StatePublished - Mar 15 2017

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

Keywords

  • Data-driven and sparsity-constrained deformable segmentation
  • Fascia lata
  • Femur extraction
  • Individual skeletal muscles
  • Inter- and intra-muscular adipose tissue
  • Joint label fusion based multi-atlas labeling
  • Radiographic knee osteoarthritis
  • Temporal related changes of thigh tissue

Fingerprint Dive into the research topics of 'Towards large-scale MR thigh image analysis via an integrated quantification framework'. Together they form a unique fingerprint.

Cite this