Performance of an automated renal segmentation algorithm based on morphological erosion and connectivity

Benjamin Abiri, Brian Park, Hersh Chandarana, Artem Mikheev, Vivian S. Lee, Henry Rusinek

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


The precision, accuracy, and efficiency of a novel semi-automated renal segmentation technique for volumetric interpolated breath-hold sequence (VIBE ) MRI sequences was analyzed using 7 clinical datasets (14 kidneys). Two observers performed whole-kidney segmentation using EdgeWave segmentation software based on constrained morphological growth. Ground truths were prepared by manual tracing of kidney on each of approximately 40 slices. Using the software, the average inter-observer disagreement was 2.7%± 2.1% for whole kidney volume, 2.1%± 1.8% for cortex, and 4.1%± 3.2% for medulla. In comparison to the ground truth kidney volume, the error was 2.8%± 2.5% for whole kidney volume, 3.1%± 1.7% for cortex, and 3.6%±.3.1% for medulla. It took an average of 4:14±1:42 minutes of operator time, plus 2:56± 1:23 minutes of computer time to perform segmentation of one whole kidney, cortex, and medulla. Segmentation speed, inter-observer agreement and accuracy were several times better than those of our existing graph-cuts segmentation technique requiring approximately 20 minutes per case and with 7-10% error. With the expedited image processing, high inter-observer agreement, and volumes closely matching true values, kidney volumetry becomes a reality in many clinical applications.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2014
Subtitle of host publicationComputer-Aided Diagnosis
ISBN (Print)9780819498281
StatePublished - 2014
Externally publishedYes
EventMedical Imaging 2014: Computer-Aided Diagnosis - San Diego, CA, United States
Duration: Feb 18 2014Feb 20 2014

Publication series

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


ConferenceMedical Imaging 2014: Computer-Aided Diagnosis
Country/TerritoryUnited States
CitySan Diego, CA


  • Computer-Aided Diagnosis
  • Image Processing
  • Image perception and observer performance
  • Kidney
  • MR-GFR
  • Renal Volumetry
  • Segmentation

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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