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Items: 1 to 20 of 105

1.

Imaging breast adipose and fibroglandular tissue molecular signatures by using hybrid MRI-guided near-infrared spectral tomography.

Brooksby B, Pogue BW, Jiang S, Dehghani H, Srinivasan S, Kogel C, Tosteson TD, Weaver J, Poplack SP, Paulsen KD.

Proc Natl Acad Sci U S A. 2006 Jun 6;103(23):8828-33. Epub 2006 May 26.

2.

Developments in quantitative oxygen-saturation imaging of breast tissue in vivo using multispectral near-infrared tomography.

Srinivasan S, Pogue BW, Carpenter C, Jiang S, Wells WA, Poplack SP, Kaufman PA, Paulsen KD.

Antioxid Redox Signal. 2007 Aug;9(8):1143-56. Review.

PMID:
17627478
3.

Combining near-infrared tomography and magnetic resonance imaging to study in vivo breast tissue: implementation of a Laplacian-type regularization to incorporate magnetic resonance structure.

Brooksby B, Jiang S, Dehghani H, Pogue BW, Paulsen KD, Weaver J, Kogel C, Poplack SP.

J Biomed Opt. 2005 Sep-Oct;10(5):051504.

PMID:
16292948
4.

MR-Guided Near-Infrared Spectral Tomography Increases Diagnostic Performance of Breast MRI.

Mastanduno MA, Xu J, El-Ghussein F, Jiang S, Yin H, Zhao Y, Wang K, Ren F, Gui J, Pogue BW, Paulsen KD.

Clin Cancer Res. 2015 Sep 1;21(17):3906-12. doi: 10.1158/1078-0432.CCR-14-2546. Epub 2015 May 27.

5.

In vivo hemoglobin and water concentrations, oxygen saturation, and scattering estimates from near-infrared breast tomography using spectral reconstruction.

Srinivasan S, Pogue BW, Jiang S, Dehghani H, Kogel C, Soho S, Gibson JJ, Tosteson TD, Poplack SP, Paulsen KD.

Acad Radiol. 2006 Feb;13(2):195-202.

PMID:
16428055
6.

Adaptable near-infrared spectroscopy fiber array for improved coupling to different breast sizes during clinical MRI.

Mastanduno MA, El-Ghussein F, Jiang S, Diflorio-Alexander R, Junqing X, Hong Y, Pogue BW, Paulsen KD.

Acad Radiol. 2014 Feb;21(2):141-50. doi: 10.1016/j.acra.2013.09.025.

7.

Magnetic-resonance-imaging-coupled broadband near-infrared tomography system for small animal brain studies.

Xu H, Springett R, Dehghani H, Pogue BW, Paulsen KD, Dunn JF.

Appl Opt. 2005 Apr 10;44(11):2177-88.

PMID:
15835363
8.

Comparison of breast density measured on MR images acquired using fat-suppressed versus nonfat-suppressed sequences.

Chang DH, Chen JH, Lin M, Bahri S, Yu HJ, Mehta RS, Nie K, Hsiang DJ, Nalcioglu O, Su MY.

Med Phys. 2011 Nov;38(11):5961-8. doi: 10.1118/1.3646756.

9.

Image-guided optical spectroscopy provides molecular-specific information in vivo: MRI-guided spectroscopy of breast cancer hemoglobin, water, and scatterer size.

Carpenter CM, Pogue BW, Jiang S, Dehghani H, Wang X, Paulsen KD, Wells WA, Forero J, Kogel C, Weaver JB, Poplack SP, Kaufman PA.

Opt Lett. 2007 Apr 15;32(8):933-5.

PMID:
17375158
10.

Rapid magnetic resonance-guided near-infrared mapping to image pulsatile hemoglobin in the breast.

Li Z, Krishnaswamy V, Jiang S, Davis SC, Srinivasan S, Paulsen KD, Pogue BW.

Opt Lett. 2010 Dec 1;35(23):3964-6. doi: 10.1364/OL.35.003964.

11.

Fatty and fibroglandular tissue volumes in the breasts of women 20-83 years old: comparison of X-ray mammography and computer-assisted MR imaging.

Lee NA, Rusinek H, Weinreb J, Chandra R, Toth H, Singer C, Newstead G.

AJR Am J Roentgenol. 1997 Feb;168(2):501-6.

PMID:
9016235
12.

Computational simulation of breast compression based on segmented breast and fibroglandular tissues on magnetic resonance images.

Shih TC, Chen JH, Liu D, Nie K, Sun L, Lin M, Chang D, Nalcioglu O, Su MY.

Phys Med Biol. 2010 Jul 21;55(14):4153-68. doi: 10.1088/0031-9155/55/14/013. Epub 2010 Jul 5.

13.

Semi-automated segmentation and classification of digital breast tomosynthesis reconstructed images.

Vedantham S, Shi L, Karellas A, Michaelsen KE, Krishnaswamy V, Pogue BW, Paulsen KD.

Conf Proc IEEE Eng Med Biol Soc. 2011;2011:6188-91. doi: 10.1109/IEMBS.2011.6091528.

14.

Automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI using an atlas-aided fuzzy C-means method.

Wu S, Weinstein SP, Conant EF, Kontos D.

Med Phys. 2013 Dec;40(12):122302. doi: 10.1118/1.4829496.

15.

Sensitivity of hemoglobin concentration on optical probe positioning in image-guided near infrared spectroscopy.

Srinivasan S, Carpenter C, Pogue BW.

Conf Proc IEEE Eng Med Biol Soc. 2009;2009:1994-6. doi: 10.1109/IEMBS.2009.5333426.

16.

Correlation between mammographic density and volumetric fibroglandular tissue estimated on breast MR images.

Wei J, Chan HP, Helvie MA, Roubidoux MA, Sahiner B, Hadjiiski LM, Zhou C, Paquerault S, Chenevert T, Goodsitt MM.

Med Phys. 2004 Apr;31(4):933-42.

17.

Image guided near-infrared spectroscopy of breast tissue in vivo using boundary element method.

Srinivasan S, Carpenter CM, Ghadyani HR, Taka SJ, Kaufman PA, Diflorio-Alexander RM, Wells WA, Pogue BW, Paulsen KD.

J Biomed Opt. 2010 Nov-Dec;15(6):061703. doi: 10.1117/1.3499419.

18.

Spectral tomography with diffuse near-infrared light: inclusion of broadband frequency domain spectral data.

Wang J, Davis SC, Srinivasan S, Jiang S, Pogue BW, Paulsen KD.

J Biomed Opt. 2008 Jul-Aug;13(4):041305. doi: 10.1117/1.2952006.

19.

Near-infrared spectral tomography integrated with digital breast tomosynthesis: effects of tissue scattering on optical data acquisition design.

Michaelsen K, Krishnaswamy V, Pogue BW, Poplack SP, Paulsen KD.

Med Phys. 2012 Jul;39(7):4579-87. doi: 10.1118/1.4728228.

20.

Quantitative analysis of breast parenchymal patterns using 3D fibroglandular tissues segmented based on MRI.

Nie K, Chang D, Chen JH, Hsu CC, Nalcioglu O, Su MY.

Med Phys. 2010 Jan;37(1):217-26.

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