20.8.3.2 Kidney Disease, Tomography, CAT Analysis, Other Methods

Chapter Contents (Back)
Reconstruction. Kidney Disease. Tomography.

Gleason, S.S., Sari-Sarraf, H., Abidi, M.A., Karakashian, O., Morandi, F.,
A new deformable model for analysis of X-ray CT images in preclinical studies of mice for polycystic kidney disease,
MedImg(21), No. 10, October 2002, pp. 1302-1309.
IEEE Top Reference. 0301
BibRef

Selfridge, P.G., Prewitt, J.M.S.,
Organ Detection in Abdominal Computerized Tomography Scans: Application to the Kidney,
CGIP(15), No. 3, March 1981, pp. 265-278.
WWW Link. BibRef 8103

Oshiro, O.[Osamu], Kamada, K.[Kumi], Imura, M.[Masataka], Chihara, K.[Kunihiro], Toyota, E.[Eiji], Ogasawara, Y.[Yasuo], Kajiya, F.[Fumihiko],
Kidney Glomerulus Observation in Interactive VR Space,
IJIG(3), No. 4, October 2003, pp. 629-637. 0310
BibRef

Xie, J.[Jun], Jiang, Y.F.[Yi-Feng], Tsui, H.T.[Hung-Tat],
Segmentation of kidney from ultrasound images based on texture and shape priors,
MedImg(24), No. 1, January 2005, pp. 45-57.
IEEE Abstract. 0501
BibRef
And: Erratum: MedImg(24), No. 2, February 2005, pp. 277-277.
IEEE Abstract. 0501
BibRef

Linguraru, M.G.[Marius George], Yao, J.H.[Jian-Hua], Gautam, R.[Rabindra], Peterson, J.[James], Li, Z.X.[Zhi-Xi], Linehan, W.M.[W. Marston], Summers, R.M.[Ronald M.],
Renal tumor quantification and classification in contrast-enhanced abdominal CT,
PR(42), No. 6, June 2009, pp. 1149-1161.
Elsevier DOI 0902
Contrast-enhanced CT; Kidney cancer; von Hippel-Lindau syndrome; Hereditary papillary renal carcinoma; Segmentation; Quantification; Classification; Monitoring; Level sets; Computer-assisted radiology BibRef

Raja, K.B.[K. Bommanna], Madheswaran, M., Thyagarajah, K.,
Texture pattern analysis of kidney tissues for disorder identification and classification using dominant Gabor wavelet,
MVA(21), No. 3, April 2010, pp. xx-yy.
Springer DOI 1003
BibRef

Gloger, O., Tonnies, K.D., Liebscher, V., Kugelmann, B., Laqua, R., Volzke, H.,
Prior Shape Level Set Segmentation on Multistep Generated Probability Maps of MR Datasets for Fully Automatic Kidney Parenchyma Volumetry,
MedImg(31), No. 2, February 2012, pp. 312-325.
IEEE DOI 1202
BibRef

Huang, J.[Jie], Yang, X.P.[Xiao-Ping], Chen, Y.M.[Yun-Mei], Tang, L.M.[Li-Ming],
Ultrasound kidney segmentation with a global prior shape,
JVCIR(24), No. 7, 2013, pp. 937-943.
Elsevier DOI 1309
Active contour BibRef

Rudra, A.K.[Ashish K.], Chowdhury, A.S.[Ananda S.], Elnakib, A.[Ahmed], Khalifa, F.[Fahmi], Soliman, A.[Ahmed], Beache, G.[Garth], El-Baz, A.[Ayman],
Kidney segmentation using graph cuts and pixel connectivity,
PRL(34), No. 13, 2013, pp. 1470-1475.
Elsevier DOI 1308
Kidney segmentation BibRef

Skounakis, E., Banitsas, K., Badii, A., Tzoulakis, S., Maravelakis, E., Konstantaras, A.,
ATD: A Multiplatform for Semiautomatic 3-D Detection of Kidneys and Their Pathology in Real Time,
HMS(44), No. 1, February 2014, pp. 146-153.
IEEE DOI 1403
biomedical MRI BibRef

Hodneland, E., Hanson, E.A., Lundervold, A., Modersitzki, J., Eikefjord, E., Munthe-Kaas, A.Z.,
Segmentation-Driven Image Registration-Application to 4D DCE-MRI Recordings of the Moving Kidneys,
IP(23), No. 5, May 2014, pp. 2392-2404.
IEEE DOI 1405
Educational institutions BibRef

Gupta, A.[Abhinav], Karmeshu,
Efficacy of Pearson distributions for characterization of gray levels in clinical ultrasound kidney images,
SIViP(9), No. 6, September 2015, pp. 1317-1334.
WWW Link. 1509
BibRef

Cerrolaza, J.J., Safdar, N., Biggs, E., Jago, J., Peters, C.A., Linguraru, M.G.,
Renal Segmentation From 3D Ultrasound via Fuzzy Appearance Models and Patient-Specific Alpha Shapes,
MedImg(35), No. 11, November 2016, pp. 2393-2402.
IEEE DOI 1609
biological tissues BibRef

Selvathi, D., Bama, S.,
Phase based distance regularized level set for the segmentation of ultrasound kidney images,
PRL(86), No. 1, 2017, pp. 9-17.
Elsevier DOI 1702
Local feature BibRef


Gadermayr, M.[Michael], Klinkhammer, B.M.[Barbara Mara], Boor, P.[Peter], Merhof, D.[Dorit],
Do We Need Large Annotated Training Data for Detection Applications in Biomedical Imaging? A Case Study in Renal Glomeruli Detection,
MLMI16(18-26).
Springer DOI 1611
BibRef

Hussain, M.A.[Mohammad Arafat], Hamarneh, G.[Ghassan], O'Connell, T.W.[Timothy W.], Mohammed, M.F.[Mohammed F.], Abugharbieh, R.[Rafeef],
Segmentation-Free Estimation of Kidney Volumes in CT with Dual Regression Forests,
MLMI16(156-163).
Springer DOI 1611
BibRef

Shehata, M.[Mohamed], Khalifa, F.[Fahmi], Soliman, A.[Ahmed], Alrefai, R.[Rahaf], El-Ghar, M.A.[Mohamed Abou], Dwyer, A.C.[Amy C.], Ouseph, R.[Rosemary], El-Baz, A.[Ayman],
A level set-based framework for 3D kidney segmentation from diffusion MR images,
ICIP15(4441-4445)
IEEE DOI 1512
Adaptive Shape; DW-MRI; Deformable Model BibRef

Khalifa, F., Soliman, A., Dwyer, A.C., Gimel'farb, G., El-Baz, A.,
A random forest-based framework for 3D kidney segmentation from dynamic contrast-enhanced CT images,
ICIP16(3399-3403)
IEEE DOI 1610
Computed tomography BibRef

Dai, G.Y.[Gao-Yuan], Li, Z.C.[Zhi-Cheng], Gu, J.[Jia], Wang, L.[Lei], Li, X.M.[Xing-Min],
Segmentation of kidneys from computed tomography using 3D fast GrowCut algorithm,
ICIP13(1144-1147)
IEEE DOI 1402
Accuracy BibRef

Landgren, M.[Matilda], Sjöstrand, K.[Karl], Ohlsson, M.[Mattias], Ståhl, D.[Daniel], Overgaard, N.C.[Niels Christian], Åström, K.[Kalle], Sixt, R.[Rune], Edenbrandt, L.[Lars],
An Automated System for the Detection and Diagnosis of Kidney Lesions in Children from Scintigraphy Images,
SCIA11(489-500).
Springer DOI 1105
BibRef

Khalifa, F., Gimel'farb, G.L., El-Ghar, M.A.[M. Abo], Sokhadze, G., Manning, S., McClure, P., Ouseph, R., El-Baz, A.,
A new deformable model-based segmentation approach for accurate extraction of the kidney from abdominal CT images,
ICIP11(3393-3396).
IEEE DOI 1201
BibRef

Strawn, N.[Nathaniel], Yao, J.H.[Jian-Hua],
Tracking kidney tumor dimensional measurements via image morphing,
ICIP10(1721-1724).
IEEE DOI 1009
BibRef

Abd el Munim, H.E., Farag, A.A.[Aly A.], Miller, W., AboelGhar, M.[Mohamed],
A kidney segmentation approach from DCE-MRI using level sets,
MMBIA08(1-6).
IEEE DOI 0806
BibRef

Boukerroui, D.[Djamal], Touhami, W.[Wala], Cocquerez, J.P.[Jean Pierre],
Automatic regions of interest identification and classification in CT images: Application to kidney cysts,
IPTA08(1-8).
IEEE DOI 0811
BibRef

Koh, H.K., Shen, W.[Weijia], Shuter, B., Kassim, A.A.,
Segmentation of Kidney Cortex in MRI Studies using a Constrained Morphological 3D H-maxima Transform,
ICARCV06(1-5).
IEEE DOI 0612
BibRef

Touhami, W., Boukerroui, D., Cocquerez, J.P.,
A Statistical Approach for Automatic Kidneys Detection,
ICIP05(III: 740-743).
IEEE DOI 0512
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Tomographic Image Generation, CAT, CT, Reconstruction .


Last update:Nov 18, 2017 at 20:56:18