Supervised segmentation of polycystic kidneys: A new application for stereology data

Joshua D. Warner; Maria V. Irazabal; Ganapathy Krishnamurthi; Bernard F. King; Vicente E. Torres; Bradley J. Erickson

doi:10.1007/s10278-014-9679-y

Supervised segmentation of polycystic kidneys: A new application for stereology data

Joshua D. Warner, Maria V. Irazabal, Ganapathy Krishnamurthi, Bernard F. King, Vicente E. Torres, Bradley J. Erickson

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

Stereology is a volume estimation method, typically applied to diagnostic imaging examinations in population studies where planimetry is too time-consuming (Chapman et al. Kidney Int 64:1035-1045, 2003), to obtain quantitative measurements (Nyengaard J Am Soc Nephrol 10:1100-1123, 1999, Michel and Cruz-Orive J Microsc 150:117-136, 1988) of certain structures or organs. However, true segmentation is required in order to perform advanced analysis of the tissues. This paper describes a novel method for segmentation of region(s) of interest using stereology data as prior information. The result is an efficient segmentation method for structures that cannot be easily segmented using other methods.

Original language	English (US)
Pages (from-to)	514-519
Number of pages	6
Journal	Journal of Digital Imaging
Volume	27
Issue number	4
DOIs	https://doi.org/10.1007/s10278-014-9679-y
State	Published - Aug 2014

Keywords

3D imaging (three-dimensional imaging)
3D segmentation
Biomedical image analysis
Boundary extraction
Data extraction
Digital image processing
Fuzzy logic
Image analysis
Image segmentation
MR imaging
Magnetic resonance imaging
Planimetry
Polycystic kidney disease
Python
Segmentation

ASJC Scopus subject areas

Radiological and Ultrasound Technology
Radiology Nuclear Medicine and imaging
Computer Science Applications

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title = "Supervised segmentation of polycystic kidneys: A new application for stereology data",

abstract = "Stereology is a volume estimation method, typically applied to diagnostic imaging examinations in population studies where planimetry is too time-consuming (Chapman et al. Kidney Int 64:1035-1045, 2003), to obtain quantitative measurements (Nyengaard J Am Soc Nephrol 10:1100-1123, 1999, Michel and Cruz-Orive J Microsc 150:117-136, 1988) of certain structures or organs. However, true segmentation is required in order to perform advanced analysis of the tissues. This paper describes a novel method for segmentation of region(s) of interest using stereology data as prior information. The result is an efficient segmentation method for structures that cannot be easily segmented using other methods.",

keywords = "3D imaging (three-dimensional imaging), 3D segmentation, Biomedical image analysis, Boundary extraction, Data extraction, Digital image processing, Fuzzy logic, Image analysis, Image segmentation, MR imaging, Magnetic resonance imaging, Planimetry, Polycystic kidney disease, Python, Segmentation",

author = "Warner, {Joshua D.} and Irazabal, {Maria V.} and Ganapathy Krishnamurthi and King, {Bernard F.} and Torres, {Vicente E.} and Erickson, {Bradley J.}",

note = "Funding Information: The authors would like to thank the NIH and NIDDK for their support under the grants F30DK098832 and P30DK090728, and Joshua Warner wishes to thank the Mayo Clinic Medical Scientist Training Program (MSTP) for fostering an outstanding environment for physician-scientist training.",

year = "2014",

month = aug,

doi = "10.1007/s10278-014-9679-y",

language = "English (US)",

volume = "27",

pages = "514--519",

journal = "Journal of Digital Imaging",

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AU - Krishnamurthi, Ganapathy

AU - King, Bernard F.

AU - Torres, Vicente E.

AU - Erickson, Bradley J.

N1 - Funding Information: The authors would like to thank the NIH and NIDDK for their support under the grants F30DK098832 and P30DK090728, and Joshua Warner wishes to thank the Mayo Clinic Medical Scientist Training Program (MSTP) for fostering an outstanding environment for physician-scientist training.

PY - 2014/8

Y1 - 2014/8

N2 - Stereology is a volume estimation method, typically applied to diagnostic imaging examinations in population studies where planimetry is too time-consuming (Chapman et al. Kidney Int 64:1035-1045, 2003), to obtain quantitative measurements (Nyengaard J Am Soc Nephrol 10:1100-1123, 1999, Michel and Cruz-Orive J Microsc 150:117-136, 1988) of certain structures or organs. However, true segmentation is required in order to perform advanced analysis of the tissues. This paper describes a novel method for segmentation of region(s) of interest using stereology data as prior information. The result is an efficient segmentation method for structures that cannot be easily segmented using other methods.

AB - Stereology is a volume estimation method, typically applied to diagnostic imaging examinations in population studies where planimetry is too time-consuming (Chapman et al. Kidney Int 64:1035-1045, 2003), to obtain quantitative measurements (Nyengaard J Am Soc Nephrol 10:1100-1123, 1999, Michel and Cruz-Orive J Microsc 150:117-136, 1988) of certain structures or organs. However, true segmentation is required in order to perform advanced analysis of the tissues. This paper describes a novel method for segmentation of region(s) of interest using stereology data as prior information. The result is an efficient segmentation method for structures that cannot be easily segmented using other methods.

KW - 3D imaging (three-dimensional imaging)

KW - 3D segmentation

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KW - Image analysis

KW - Image segmentation

KW - MR imaging

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KW - Planimetry

KW - Polycystic kidney disease

KW - Python

KW - Segmentation

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Supervised segmentation of polycystic kidneys: A new application for stereology data

Abstract

Keywords

ASJC Scopus subject areas

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