Literature DB >> 15008484

Automated region detection based on the contrast-to-noise ratio in near-infrared tomography.

Xiaomei Song1, Brian W Pogue, Shudong Jiang, Marvin M Doyley, Hamid Dehghani, Tor D Tosteson, Keith D Paulsen.   

Abstract

The contrast-to-noise ratio (CNR) was used to determine the detectability of objects within reconstructed images from diffuse near-infrared tomography. It was concluded that there was a maximal value of CNR near the location of an object within the image and that the size of the true region could be estimated from the CNR. Experimental and simulation studies led to the conclusion that objects can be automatically detected with CNR analysis and that our current system has a spatial resolution limit near 4 mm and a contrast resolution limit near 1.4. A new linear convolution method of CNR calculation was developed for automated region of interest (ROI) detection.

Mesh:

Year:  2004        PMID: 15008484     DOI: 10.1364/ao.43.001053

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  34 in total

1.  Volumetric elasticity imaging with a 2-D CMUT array.

Authors:  Ted G Fisher; Timothy J Hall; Satchi Panda; Michael S Richards; Paul E Barbone; Jingfeng Jiang; Jeff Resnick; Steve Barnes
Journal:  Ultrasound Med Biol       Date:  2010-06       Impact factor: 2.998

2.  Comprehensive investigation of three-dimensional diffuse optical tomography with depth compensation algorithm.

Authors:  Haijing Niu; Zi-Jing Lin; Fenghua Tian; Sameer Dhamne; Hanli Liu
Journal:  J Biomed Opt       Date:  2010 Jul-Aug       Impact factor: 3.170

3.  Quantification and normalization of noise variance with sparsity regularization to enhance diffuse optical tomography.

Authors:  Jixing Yao; Fenghua Tian; Yothin Rakvongthai; Soontorn Oraintara; Hanli Liu
Journal:  Biomed Opt Express       Date:  2015-07-20       Impact factor: 3.732

4.  Nonuniform update for sparse target recovery in fluorescence molecular tomography accelerated by ordered subsets.

Authors:  Dianwen Zhu; Changqing Li
Journal:  Biomed Opt Express       Date:  2014-11-12       Impact factor: 3.732

5.  Computer-aided diagnosis of rheumatoid arthritis with optical tomography, Part 1: feature extraction.

Authors:  Ludguier D Montejo; Jingfei Jia; Hyun K Kim; Uwe J Netz; Sabine Blaschke; Gerhard A Müller; Andreas H Hielscher
Journal:  J Biomed Opt       Date:  2013-07       Impact factor: 3.170

6.  Computer aided automatic detection of malignant lesions in diffuse optical mammography.

Authors:  David R Busch; Wensheng Guo; Regine Choe; Turgut Durduran; Michael D Feldman; Carolyn Mies; Mark A Rosen; Mitchell D Schnall; Brian J Czerniecki; Julia Tchou; Angela DeMichele; Mary E Putt; Arjun G Yodh
Journal:  Med Phys       Date:  2010-04       Impact factor: 4.071

7.  Relative Elastic Modulus Imaging Using Sector Ultrasound Data for Abdominal Applications: An Evaluation of Strategies and Feasibility.

Authors:  Bo Peng; Yu Wang; Wenjun Yang; Tomy Varghese; Jingfeng Jiang
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2016-07-09       Impact factor: 2.725

8.  Ultrasound-based relative elastic modulus imaging for visualizing thermal ablation zones in a porcine model.

Authors:  Jingfeng Jiang; Chris Brace; Anita Andreano; Ryan J DeWall; Nick Rubert; Ted G Fisher; Tomy Varghese; Fred Lee; Timothy J Hall
Journal:  Phys Med Biol       Date:  2010-03-30       Impact factor: 3.609

9.  A PDE-Based Regularization Algorithm Toward Reducing Speckle Tracking Noise: A Feasibility Study for Ultrasound Breast Elastography.

Authors:  Li Guo; Yan Xu; Zhengfu Xu; Jingfeng Jiang
Journal:  Ultrason Imaging       Date:  2014-11-30       Impact factor: 1.578

10.  Neural-network-based Motion Tracking for Breast Ultrasound Strain Elastography: An Initial Assessment of Performance and Feasibility.

Authors:  Bo Peng; Yuhong Xian; Quan Zhang; Jingfeng Jiang
Journal:  Ultrason Imaging       Date:  2020-01-30       Impact factor: 1.578

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