|
1
|
Yang M, Gao F, Liu H, Pang H, Zuo YP and
Yong T: Prospectively estimating the recoverability of renal
function after relief of unilateral urinary obstruction by
measurement of renal parenchymal volume. Acad Radiol. 20:401–406.
2013. View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Gupta S, Singh AH, Shabbir A, Hahn PF,
Harris G and Sahani D: Assessing renal parenchymal volume on
unenhanced CT as a marker for predicting renal function in patients
with chronic kidney disease. Acad Radiol. 19:654–660. 2012.
View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Yano M, Lin MF, Hoffman KA, Vijayan A,
Pilgram TK and Narra VR: Renal measurements on CT angiograms:
Correlation with graft function at living donor renal
transplantation. Radiology. 265:151–157. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Sharma N, O'Hara J, Novick AC, Lieber M,
Remer EM and Herts BR: Correlation between loss of renal function
and loss of renal volume after partial nephrectomy for tumor in a
solitary kidney. J Urol. 179:1284–1288. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
Sommer G, Bouley D, Frisoli J, Pierce L,
Sandner-Porkristl D and Fahrig R: Determination of 3-dimensional
zonal renal volumes using contrast-enhanced computed tomography. J
Comput Assist Tomogr. 31:209–213. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
6
|
Bakker J, Olree M, Kaatee R, de Lange EE,
Moons KG, Beutler JJ and Beek FJ: Renal volume measurements:
Accuracy and repeatability of US compared with that of MR imaging.
Radiology. 211:623–628. 1999. View Article : Google Scholar : PubMed/NCBI
|
|
7
|
Partik BL, Stadler A, Schamp S, Koller A,
Voracek M, Heinz G and Helbich TH: 3D versus 2D ultrasound:
Accuracy of volume measurement in human cadaver kidneys. Invest
Radiol. 37:489–495. 2002. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Gandy SJ, Armoogum K, Nicholas RS, McLeay
TB and Houston JG: A clinical MRI investigation of the relationship
between kidney volume measurements and renal function in patients
with renovascular disease. Br J Radiol. 80:12–20. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Zöllner FG, Svarstad E, Munthe-Kaas AZ,
Schad LR, Lundervold A and Rørvik J: Assessment of kidney volumes
from MRI: Acquisition and segmentation techniques. AJR Am J
Roentgenol. 199:1060–1069. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
10
|
Rusinek H, Boykov Y, Kaur M, Wong S,
Bokacheva L, Sajous JB, Huang AJ, Heller S and Lee VS: Performance
of an automated segmentation algorithm for 3D MR renography. Magn
Reson Med. 57:1159–1167. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
11
|
Summerlin AL, Lockhart ME, Strang AM,
Kolettis PN, Fineberg NS and Smith JK: Determination of split renal
function by 3D reconstruction of CT angiograms: A comparison with
gamma camera renography. AJR Am J Roentgenol. 191:1552–1558. 2008.
View Article : Google Scholar : PubMed/NCBI
|
|
12
|
Widjaja E, Oxtoby JW, Hale TL, Jones PW,
Harden PN and McCall IW: Ultrasound measured renal length versus
low dose CT volume in predicting single kidney glomerular
filtration rate. Br J Radiol. 77:759–764. 2004. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Lin DT, Lei CC and Hung SW: Computer-aided
kidney segmentation on abdominal CT images. IEEE Trans Inf Technol
Biomed. 10:59–65. 2006. View Article : Google Scholar : PubMed/NCBI
|
|
14
|
Rao M, Stough J, Chi YY, Muller K, Tracton
G, Pizer SM and Chaney EL: Comparison of human and automatic
segmentations of kidneys from CT images. Int J Radiat Oncol Biol
Phys. 61:954–960. 2005. View Article : Google Scholar : PubMed/NCBI
|
|
15
|
Brown MS, Feng WC, Hall TR, Mcnitt-Gray MF
and Churchill BM: Knowledge-based segmentation of pediatric kidneys
in CT for measurement of parenchymal volume. J Comput Assist
Tomogr. 25:639–648. 2001. View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Ko JP, Rusinek H, Jacobs EL, Babb JS,
Betke M, McGuinness G and Naidich DP: Small pulmonary nodules:
Volume measurement at chest CT-phantom study. Radiology.
228:864–870. 2003. View Article : Google Scholar : PubMed/NCBI
|
|
17
|
Way TW, Chan HP, Goodsitt MM, Sahiner B,
Hadjiiski LM, Zhou C and Chughtai A: Effect of CT scanning
parameters on volumetric measurements of pulmonary nodules by 3D
active contour segmentation: A phantom study. Phys Med Biol.
53:1295–1312. 2008. View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Larici AR, Storto ML, Torge M, Mereu M,
Molinari F, Maggi F and Bonomo L: Automated volumetry of pulmonary
nodules on multidetector CT: Influence of slice thickness,
reconstruction algorithm and tube current. Preliminary results.
Radiol Med. 113:29–42. 2008.(In English, Italian). View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Muto NS, Kamishima T, Harris AA, Kato F,
Onodera Y, Terae S and Shirato H: Renal cortical volume measured
using automatic contouring software for computed tomography and its
relationship with BMI, age and renal function. Eur J Radiol.
78:151–156. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
20
|
Heckel F, Meine H, Moltz JH, Kuhnigk JM,
Heverhagen JT, Kiessling A, Buerke B and Hahn HK:
Segmentation-based partial volume correction for volume estimation
of solid lesions in CT. IEEE Trans Med Imaging. 33:462–480. 2014.
View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Kass M, Witkin A and Terzopoulos D:
Snakes: Active contour models. Int J Comput Vision. 1:321–331.
1988. View Article : Google Scholar
|
|
22
|
Heckel F, Konrad O and Peitgen HO: Fast
and smooth interactive segmentation of medical images using
variational interpolation. Proceedings of the Eurographics Workshop
on Visual Computing for Biology and Medicine. VCBM. (Leipzig).
9–16. 2010.
|
|
23
|
Chul Kim J: Animal study of renal volume
measurement on abdominal CT using digital image processing;
Preliminary report. Clin Imaging. 28:135–137. 2004. View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Cai W, Holalkere NS, Harris G, Sahani D
and Yoshida H: Dynamic-threshold level set method for volumetry of
porcine kidney in CT images in vivo and ex vivo assessment of the
accuracy of volume measurement. Acad Radiol. 14:890–896. 2007.
View Article : Google Scholar : PubMed/NCBI
|
|
25
|
Bevelacqua JJ: Practical and effective
ALARA. Health Phys 98 Suppl. 2:S39–S47. 2010. View Article : Google Scholar
|
|
26
|
Dong F, Davros W, Pozzuto J and Reid J:
Optimization of kilovoltage and tube current-exposure time product
based on abdominal circumference: An oval phantom study for
pediatric abdominal CT. AJR Am J Roentgenol. 199:670–676. 2012.
View Article : Google Scholar : PubMed/NCBI
|
|
27
|
Nakaura T, Awai K, Oda S, Funama Y, Harada
K, Uemura S and Yamashita Y: Low-kilovoltage, high-tube-current
MDCT of liver in thin adults: Pilot study evaluating radiation
dose, image quality and display settings. AJR Am J Roentgenol.
196:1332–1338. 2011. View Article : Google Scholar : PubMed/NCBI
|
|
28
|
Marin D, Nelson RC, Schindera ST, Richard
S, Youngblood RS, Yoshizumi TT and Samei E: Low-tube-voltage,
high-tube-current multidetector abdominal CT: Improved image
quality and decreased radiation dose with adaptive statistical
iterative reconstruction algorithm-initial clinical experience.
Radiology. 254:145–153. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
29
|
Nakaura T, Nakamura S, Maruyama N, Funama
Y, Awai K, Harada K, Uemura S and Yamashita Y: Low contrast agent
and radiation dose protocol for hepatic dynamic CT of thin adults
at 256-detector row CT: Effect of low tube voltage and hybrid
iterative reconstruction algorithm on image quality. Radiology.
264:445–454. 2012. View Article : Google Scholar : PubMed/NCBI
|
|
30
|
Coppenrath E, Meindl T, Herzog P, Khalil
R, Mueller-Lisse U, Krenn L, Reiser M and Mueller-Lisse UG: Dose
reduction in multidetector CT of the urinary tract. Studies in a
phantom model. Eur Radiol. 16:1982–1989. 2006. View Article : Google Scholar : PubMed/NCBI
|
