Abstract

Measuring the glomerular number in the entire, intact kidney using non-destructive techniques is of immense importance in studying several renal and systemic diseases. Commonly used approaches either require destruction of the entire kidney or perform extrapolation from measurements obtained from a few isolated sections. A recent magnetic resonance imaging (MRI) method, based on the injection of a contrast agent (cationic ferritin), has been used to effectively identify glomerular regions in the kidney. In this work, we propose a robust, accurate, and low-complexity method for estimating the number of glomeruli from such kidney MRI images. The proposed technique has a training phase and a low-complexity testing phase. In the training phase, organ segmentation is performed on a few expert-marked training images, and glomerular and non-glomerular image patches are extracted. Using non-local sparse coding to compute similarity and dissimilarity graphs between the patches, the subspace in which the glomerular regions can be discriminated from the rest are estimated. For novel test images, the image patches extracted after pre-processing are embedded using the discriminative subspace projections. The testing phase is of low computational complexity since it involves only matrix multiplications, clustering, and simple morphological operations. Preliminary results with MRI data obtained from five kidneys of rats show that the proposed non-invasive, low-complexity approach performs comparably to conventional approaches such as acid maceration and stereology.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2016
Subtitle of host publicationImage Processing
EditorsMartin A. Styner, Elsa D. Angelini, Elsa D. Angelini
PublisherSPIE
ISBN (Electronic)9781510600195
DOIs
StatePublished - 2016
EventMedical Imaging 2016: Image Processing - San Diego, United States
Duration: Mar 1 2016Mar 3 2016

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume9784
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2016: Image Processing
CountryUnited States
CitySan Diego
Period3/1/163/3/16

Keywords

  • Discriminative embedding
  • Magnetic resonance imaging
  • Non-destructive technique
  • Renal disease
  • Sparse coding

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Thiagarajan, J. J., Natesan Ramamurthy, K., Kanberoglu, B., Frakes, D., Bennett, K., & Spanias, A. (2016). Measuring glomerular number from kidney MRI images. In M. A. Styner, E. D. Angelini, & E. D. Angelini (Eds.), Medical Imaging 2016: Image Processing [978412] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9784). SPIE. https://doi.org/10.1117/12.2216753