A stochastic approach to 3-D image modeling

Dhiraj Joshi; Jia Li; James Z. Wang

doi:10.1109/LSSA.2006.250410

A stochastic approach to 3-D image modeling

Dhiraj Joshi
, Jia Li
, James Z. Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Statistical modeling methods have been success-fully used to segment, classify, and annotate digital images, over the years. In this paper, we present a 3-D hidden Markov model (HMM) for volume image modeling. The 3-D HMM is applied to volume image segmentation and tested using synthetic images with ground truth. Potential applications to 3-D biomedical image analysis are also discussed.

Original language	English (US)
Title of host publication	2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006
DOIs	https://doi.org/10.1109/LSSA.2006.250410
State	Published - 2006
Event	2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006 - Bethesda, MD, United States Duration: Jul 13 2006 → Jul 14 2006

Publication series

Name	2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006

Other

Other	2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006
Country/Territory	United States
City	Bethesda, MD
Period	7/13/06 → 7/14/06

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

Health(social science)
Assessment and Diagnosis
General Medicine
Health Information Management
Electrical and Electronic Engineering
Human-Computer Interaction
Computer Science Applications
Signal Processing

Access to Document

10.1109/LSSA.2006.250410

Cite this

@inproceedings{ccf67971747c4ae99aa1b221a37ff532,

title = "A stochastic approach to 3-D image modeling",

abstract = "Statistical modeling methods have been success-fully used to segment, classify, and annotate digital images, over the years. In this paper, we present a 3-D hidden Markov model (HMM) for volume image modeling. The 3-D HMM is applied to volume image segmentation and tested using synthetic images with ground truth. Potential applications to 3-D biomedical image analysis are also discussed.",

author = "Dhiraj Joshi and Jia Li and Wang, \{James Z.\}",

year = "2006",

doi = "10.1109/LSSA.2006.250410",

language = "English (US)",

isbn = "1424402786",

series = "2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006",

booktitle = "2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006",

}

Joshi, D, Li, J & Wang, JZ 2006, A stochastic approach to 3-D image modeling. in 2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006., 4015811, 2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006, 2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006, Bethesda, MD, United States, 7/13/06. https://doi.org/10.1109/LSSA.2006.250410

TY - GEN

T1 - A stochastic approach to 3-D image modeling

AU - Joshi, Dhiraj

AU - Li, Jia

AU - Wang, James Z.

PY - 2006

Y1 - 2006

N2 - Statistical modeling methods have been success-fully used to segment, classify, and annotate digital images, over the years. In this paper, we present a 3-D hidden Markov model (HMM) for volume image modeling. The 3-D HMM is applied to volume image segmentation and tested using synthetic images with ground truth. Potential applications to 3-D biomedical image analysis are also discussed.

AB - Statistical modeling methods have been success-fully used to segment, classify, and annotate digital images, over the years. In this paper, we present a 3-D hidden Markov model (HMM) for volume image modeling. The 3-D HMM is applied to volume image segmentation and tested using synthetic images with ground truth. Potential applications to 3-D biomedical image analysis are also discussed.

UR - https://www.scopus.com/pages/publications/42749099853

UR - https://www.scopus.com/pages/publications/42749099853#tab=citedBy

U2 - 10.1109/LSSA.2006.250410

DO - 10.1109/LSSA.2006.250410

M3 - Conference contribution

AN - SCOPUS:42749099853

SN - 1424402786

SN - 9781424402786

T3 - 2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006

BT - 2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006

T2 - 2006 IEEE/NLM Life Science Systems and Applications Workshop, LiSA 2006

Y2 - 13 July 2006 through 14 July 2006

ER -

A stochastic approach to 3-D image modeling

Abstract

Publication series

Other

UN SDGs

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this