21.8.3.1 Abdominal Seqmentation, Multi-Organ Segmentation

Chapter Contents (Back)
Reconstruction. Abdominal Analysis. Tomography.
See also Liver Disease, Tomography, CAT Analysis.
See also Kidney Disease, Tomography, CAT Analysis, Other Methods.

Koss, J.E., Newman, F.D., Johnson, T.K., Kirch, D.L.,
Abdominal organ segmentation using texture transforms and a Hopfield neural network,
MedImg(18), No. 7, July 1999, pp. 640-648.
IEEE Top Reference. 0110
BibRef

Park, H.J.[Hyun-Jin], Bland, P.H., Meyer, C.R.,
Construction of an abdominal probabilistic atlas and its application in segmentation,
MedImg(22), No. 4, April 2003, pp. 483-492.
IEEE Abstract. 0306
BibRef

Kamiya, N.[Naoki], Zhou, X.R.[Xiang-Rong], Chen, H.Y.[Hua-Yue], Muramatsu, C.[Chisako], Hara, T.[Takeshi], Fujita, H.[Hiroshi],
Model-Based Approach to Recognize the Rectus Abdominis Muscle in CT Images,
IEICE(E96-D), No. 4, April 2013, pp. 869-871.
WWW Link. 1304
BibRef

Wolz, R., Chu, C., Misawa, K., Fujiwara, M., Mori, K., Rueckert, D.,
Automated Abdominal Multi-Organ Segmentation With Subject-Specific Atlas Generation,
MedImg(32), No. 9, 2013, pp. 1723-1730.
IEEE DOI 1309
Abdominal computed tomography (CT) BibRef

Bhole, C.[Chetan], Pal, C.[Christopher], Rim, D.[David], Wismüller, A.[Axel],
3D segmentation of abdominal CT imagery with graphical models, conditional random fields and learning,
MVA(25), No. 2, February 2014, pp. 301-325.
WWW Link. 1402
BibRef

Rister, B., Horowitz, M.A., Rubin, D.L.,
Volumetric Image Registration From Invariant Keypoints,
IP(26), No. 10, October 2017, pp. 4900-4910.
IEEE DOI 1708
affine transforms, computerised tomography, image registration, 3D scale-invariant keypoints, SIFT, abdominal CT images, affine transforms, discrete extrema detection, gradient histograms, head MR images, keypoint matching, orientation assignment, rotation-invariant keypoints, scale invariant feature transform, volumetric image registration, Biomedical imaging, Head, Histograms, Image registration, Tensile stress, 3D SIFT, magnetic resonance imaging (MRI), registration BibRef

Ma, J.[Jun], Zhang, Y.[Yao], Gu, S.[Song], Zhu, C.[Cheng], Ge, C.[Cheng], Zhang, Y.[Yichi], An, X.L.[Xing-Le], Wang, C.C.[Cong-Cong], Wang, Q.Y.[Qi-Yuan], Liu, X.[Xin], Cao, S.C.[Shu-Cheng], Zhang, Q.[Qi], Liu, S.Q.[Shang-Qing], Wang, Y.P.[Yun-Peng], Li, Y.H.[Yu-Hui], He, J.[Jian], Yang, X.P.[Xiao-Ping],
AbdomenCT-1K: Is Abdominal Organ Segmentation a Solved Problem?,
PAMI(44), No. 10, October 2022, pp. 6695-6714.
IEEE DOI 2209
Benchmark testing, Liver, Image segmentation, Biological systems, Pancreas, Computed tomography, Kidney, Multi-organ segmentation, continual learning BibRef

Chen, D.[Duowen], Bai, Y.H.[Yun-Hao], Shen, W.[Wei], Li, Q.L.[Qing-Li], Yu, L.[Lequan], Wang, Y.[Yan],
MagicNet: Semi-Supervised Multi-Organ Segmentation via Magic-Cube Partition and Recovery,
CVPR23(23869-23878)
IEEE DOI 2309
BibRef

Feng, Z.H.[Zheng-Hao], Wen, L.[Lu], Yan, B.[Binyu], Cui, J.Q.[Jia-Qi], Wang, Y.[Yan],
Alleviating Class Imbalance in Semi-Supervised Multi-Organ Segmentation via Balanced Subclass Regularization,
SPLetters(31), 2024, pp. 2450-2454.
IEEE DOI 2410
Task analysis, Decoding, Data models, Image segmentation, Multitasking, Knowledge engineering, Accuracy, semi-supervised learning BibRef

Zhou, Y.Y.[Yu-Yin], Wang, Y.[Yan], Tang, P.[Peng], Bai, S.[Song], Shen, W.[Wei], Fishman, E.[Elliot], Yuille, A.L.[Alan L.],
Semi-Supervised 3D Abdominal Multi-Organ Segmentation Via Deep Multi-Planar Co-Training,
WACV19(121-140)
IEEE DOI 1904
image segmentation, medical image processing, neural nets, supervised learning, multiplanar fusion, deep network, Computed tomography BibRef


Kuanar, S., Athitsos, V., Mahapatra, D., Rao, K.R., Akhtar, Z., Dasgupta, D.,
Low Dose Abdominal CT Image Reconstruction: An Unsupervised Learning Based Approach,
ICIP19(1351-1355)
IEEE DOI 1910
Auto-encoder, Low dose CT Image, De-noise, Manifold, and GAN BibRef

Wang, Z., Liu, Z., Song, Y., Zhu, Y.,
Densely connected deep U-Net for abdominal multi-organ segmentation,
ICIP19(1415-1419)
IEEE DOI 1910
Multiple organ segmentation, DC U-Net, dense connection, small sample segmentation, feature information BibRef

Akbar, M.U.[Muhammad Usman], Yamin, M.A.[Muhammad Abubakar], Murino, V.[Vittorio], Sona, D.[Diego],
Organ Segmentation with Recursive Data Augmentation for Deep Models,
AIHA20(337-343).
Springer DOI 2103
BibRef

Akbar, M.U.[Muhammad Usman], Aslani, S.[Shahab], Murino, V.[Vitorio], Sona, D.[Diego],
Multiple Organs Segmentation in Abdomen CT Scans Using a Cascade of CNNs,
CIAP19(I:509-516).
Springer DOI 1909
BibRef

Zhao, Y., Li, H., Zhou, R., Tetteh, G., Niethammer, M., Menze, B.H.,
Automatic Multi-Atlas Segmentation for Abdominal Images Using Template Construction and Robust Principal Component Analysis,
ICPR18(3880-3885)
IEEE DOI 1812
Training, Image segmentation, Principal component analysis, Pipelines, Sparse matrices, Forestry, Biomedical imaging BibRef

Larsson, M.[Mċns], Zhang, Y.H.[Yu-Hang], Kahl, F.[Fredrik],
Robust Abdominal Organ Segmentation Using Regional Convolutional Neural Networks,
SCIA17(II: 41-52).
Springer DOI 1706
BibRef

Inoue, T.[Tsutomu], Kitamura, Y.[Yoshiro], Li, Y.Z.[Yuan-Zhong], Ito, W.[Wataru], Ishikawa, H.[Hiroshi],
Psoas Major Muscle Segmentation Using Higher-Order Shape Prior,
MCV15(116-124).
Springer DOI 1608
abdominal CT images BibRef

Zografos, V.[Vasileios], Valentinitsch, A.[Alexander], Rempfler, M.[Markus], Tombari, F.[Federico], Menze, B.H.[Bjoern H.],
Hierarchical Multi-Organ Segmentation Without Registration in 3D Abdominal CT Images,
MCV15(37-46).
Springer DOI 1608
BibRef

Makrogiannis, S.[Sokratis], Ramachandran, R.[Ramona], Chia, C.W.[Chee W.], Ferrucci, L.[Luigi],
Automated abdominal fat quantification and food residue removal in CT,
MMBIA12(81-86).
IEEE DOI 1203
BibRef

Bano, J., Hostettler, A., Nicolau, S.A., Doignon, C., Wu, H.S., Huang, M.H., Soler, L., Marescaux, J.,
Simulation of the Abdominal Wall and Its Arteries after Pneumoperitoneum for Guidance of Port Positioning in Laparoscopic Surgery,
ISVC12(I: 1-11).
Springer DOI 1209
BibRef

Song, S.M.[Soo-Min], Kim, M.H.[Myoung-Hee],
Segmentation of Abdominal Organs Incorporating Prior Knowledge in Small Animal CT,
ISVC10(III: 209-218).
Springer DOI 1011
BibRef

Ding, F.[Feng], Leow, W.K.[Wee Kheng], Venkatesh, S.[Sudhakar],
Removal of abdominal wall for 3D visualization and segmentation of organs in CT volume,
ICIP09(3377-3380).
IEEE DOI 0911
BibRef

Pednekar, A.S.[Amol S.], Bandekar, A.N.[Alok N.], Kakadiaris, I.A.[Ioannis A.], Naghavi, M.[Morteza],
Automatic Segmentation of Abdominal Fat from CT Data,
WACV05(I: 308-315).
IEEE DOI 0502
BibRef

Kaneko, T., Gu, L., Fujimoto, H.,
Abdominal Organ Recognition Using 3d Mathematical Morphology,
ICPR00(Vol II: 263-266).
IEEE DOI 0009
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Liver Disease, Tomography, CAT Analysis .


Last update:Sep 28, 2024 at 17:47:54