21.10.1 Heart, Cardiac Analysis using MRI Analysis, Cardiac MRI

Oksuz, I.[Ilkay], Mukhopadhyay, A.[Anirban], Dharmakumar, R.[Rohan], Tsaftaris, S.A.[Sotirios A.],
Unsupervised Myocardial Segmentation for Cardiac BOLD,
MedImg(36), No. 11, November 2017, pp. 2228-2238.
IEEE DOI 1711
Dictionaries, Image segmentation, Magnetic resonance imaging, Manuals, Motion segmentation, Myocardium, Standards, BOLD, CINE, Unsupervised segmentation, cardiac MRI, dictionary learning, optical, flow BibRef

Mukhopadhyay, A.[Anirban], Oksuz, I.[Ilkay], Bevilacqua, M.[Marco], Dharmakumar, R.[Rohan], Tsaftaris, S.A.[Sotirios A.],
Data-Driven Feature Learning for Myocardial Segmentation of CP-BOLD MRI,
FIMH15(189-197).
Springer DOI 1507
BibRef

Odille, F., Menini, A., Escanye, J.M., Vuissoz, P.A., Marie, P.Y., Beaumont, M., Felblinger, J.,
Joint Reconstruction of Multiple Images and Motion in MRI: Application to Free-Breathing Myocardial T_2 Quantification,
MedImg(35), No. 1, January 2016, pp. 197-207.
IEEE DOI 1601
Image reconstruction BibRef

Yang, X., Su, Y., Duan, R., Fan, H., Yeo, S.Y., Lim, C., Zhong, L., Tan, R.S.,
Cardiac image segmentation by random walks with dynamic shape constraint,
IET-CV(10), No. 1, 2016, pp. 79-86.
DOI Link 1601
biomedical MRI BibRef

Tuyisenge, V., Sarry, L., Corpetti, T., Innorta-Coupez, E., Ouchchane, L., Cassagnes, L.,
Estimation of Myocardial Strain and Contraction Phase From Cine MRI Using Variational Data Assimilation,
MedImg(35), No. 2, February 2016, pp. 442-455.
IEEE DOI 1602
Data assimilation BibRef

Wech, T., Seiberlich, N., Schindele, A., Grau, V., Diffley, L., Gyngell, M.L., Borzì, A., Köstler, H., Schneider, J.E.,
Development of Real-Time Magnetic Resonance Imaging of Mouse Hearts at 9.4 Tesla: Simulations and First Application,
MedImg(35), No. 3, March 2016, pp. 912-920.
IEEE DOI 1603
Compressed sensing BibRef

Hamilton, J.I., Seiberlich, N.,
Machine Learning for Rapid Magnetic Resonance Fingerprinting Tissue Property Quantification,
PIEEE(108), No. 1, January 2020, pp. 69-85.
IEEE DOI 2001
Biological tissues, Machine learning, Magnetic resonance imaging, Mathematical model, Magnetic properties, Cardiology, tissue characterization BibRef

Chen, Y.N.[Yan-Nan], Dai, Y.H.[Yu-Hong], Han, D.R.[De-Ren],
Fiber Orientation Distribution Estimation Using a Peaceman-Rachford Splitting Method,
SIIMS(9), No. 2, 2016, pp. 573-604.
DOI Link 1608
BibRef

Bueno-Orovio, A., Teh, I., Schneider, J.E., Burrage, K., Grau, V.,
Anomalous Diffusion in Cardiac Tissue as an Index of Myocardial Microstructure,
MedImg(35), No. 9, September 2016, pp. 2200-2207.
IEEE DOI 1609
Cardiac tissue BibRef

Wang, V.Y., Casta, C., Zhu, Y.M., Cowan, B.R., Croisille, P., Young, A.A., Clarysse, P., Nash, M.P.[Martyn P.],
Image-Based Investigation of Human in Vivo Myofibre Strain,
MedImg(35), No. 11, November 2016, pp. 2486-2496.
IEEE DOI 1609
biological tissues BibRef

Bates, J.[Joanne], Teh, I.[Irvin], McClymont, D., Kohl, P.[Peter], Schneider, J.E.[Jürgen E.], Grau, V.[Vicente],
Monte Carlo Simulations of Diffusion Weighted MRI in Myocardium: Validation and Sensitivity Analysis,
MedImg(36), No. 6, June 2017, pp. 1316-1325.
IEEE DOI 1706
BibRef
Earlier: A1, A2, A4, A5, A6, Only:
Sensitivity Analysis of Diffusion Tensor MRI in Simulated Rat Myocardium,
FIMH15(120-128).
Springer DOI 1507
Analytical models, Data models, Heart, Integrated circuit modeling, Magnetic resonance imaging, Myocardium, Solid modeling, MRI, diffusion weighted imaging, heart, tissue, modelling BibRef

de Vos, B.D., Wolterink, J.M.[Jelmer M.], de Jong, P.A., Leiner, T.[Tim], Viergever, M.A.[Max A.], Išgum, I.,
ConvNet-Based Localization of Anatomical Structures in 3-D Medical Images,
MedImg(36), No. 7, July 2017, pp. 1470-1481.
IEEE DOI 1707
Abdomen, Anatomical structure, Computed tomography, Heart, CT, Localization, convolutional neural networks, deep learning, detection BibRef

Wolterink, J.M.[Jelmer M.], Leiner, T.[Tim], Viergever, M.A.[Max A.], Išgum, I.[Ivana],
Dilated Convolutional Neural Networks for Cardiovascular MR Segmentation in Congenital Heart Disease,
RAMBO16(95-102).
Springer DOI 1703
BibRef

Xue, W., Islam, A., Bhaduri, M., Li, S.,
Direct Multitype Cardiac Indices Estimation via Joint Representation and Regression Learning,
MedImg(36), No. 10, October 2017, pp. 2057-2067.
IEEE DOI 1710
biomedical MRI, cardiology, diseases, image coding, medical neural nets, regression analysis, Indices-Net, LV wall thicknesses(1.44, ROI cropping, areas-of-cavity, cardiac MR sequences, cardiac disease diagnosis, BibRef

Zhou, Y., Giffard-Roisin, S., de Craene, M., Camarasu-Pop, S., d'Hooge, J., Alessandrini, M., Friboulet, D., Sermesant, M., Bernard, O.,
A Framework for the Generation of Realistic Synthetic Cardiac Ultrasound and Magnetic Resonance Imaging Sequences From the Same Virtual Patients,
MedImg(37), No. 3, March 2018, pp. 741-754.
IEEE DOI 1804
biomechanics, biomedical MRI, cardiovascular system, deformation, diseases, echocardiography, image motion analysis, image sequences, synthetic sequences BibRef

Duchateau, N., Sermesant, M., Delingette, H., Ayache, N.,
Model-Based Generation of Large Databases of Cardiac Images: Synthesis of Pathological Cine MR Sequences From Real Healthy Cases,
MedImg(37), No. 3, March 2018, pp. 755-766.
IEEE DOI 1804
biomedical MRI, cardiology, feature extraction, image registration, image sequences, learning (artificial intelligence), validation BibRef

Bernard, O., Lalande, A., Zotti, C., Cervenansky, F., Yang, X., Heng, P., Cetin, I., Lekadir, K., Camara, O., Gonzalez Ballester, M.A., Sanroma, G., Napel, S., Petersen, S., Tziritas, G., Grinias, E., Khened, M., Kollerathu, V.A., Krishnamurthi, G., Rohé, M., Pennec, X., Sermesant, M., Isensee, F., Jäger, P., Maier-Hein, K.H., Full, P.M., Wolf, I., Engelhardt, S., Baumgartner, C.F., Koch, L.M., Wolterink, J.M., Išgum, I., Jang, Y., Hong, Y., Patravali, J., Jain, S., Humbert, O., Jodoin, P.,
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?,
MedImg(37), No. 11, November 2018, pp. 2514-2525.
IEEE DOI 1811
Machine learning, Magnetic resonance imaging, Myocardium, Image segmentation, Task analysis, Biomedical imaging, Heart, myocardium BibRef

Wigen, M.S., Fadnes, S., Rodriguez-Molares, A., Bjåstad, T., Eriksen, M., Stensæth, K.H., Støylen, A., Lovstakken, L.,
4-D Intracardiac Ultrasound Vector Flow Imaging-Feasibility and Comparison to Phase-Contrast MRI,
MedImg(37), No. 12, December 2018, pp. 2619-2629.
IEEE DOI 1812
Imaging, Blood, Ultrasonic imaging, Estimation, Kernel, Ultrasonic variables measurement, 4D ultrasound BibRef

Tarroni, G., Oktay, O., Bai, W., Schuh, A., Suzuki, H., Passerat-Palmbach, J., de Marvao, A., O'Regan, D.P., Cook, S., Glocker, B., Matthews, P.M., Rueckert, D.,
Learning-Based Quality Control for Cardiac MR Images,
MedImg(38), No. 5, May 2019, pp. 1127-1138.
IEEE DOI 1905
Heart, Quality control, Pipelines, Estimation, Motion detection, Forestry, Visualization, Image quality assessment, heart BibRef

Mohsin, Y.Q., Poddar, S., Jacob, M.,
Free-Breathing Ungated Cardiac MRI Using Iterative SToRM (i-SToRM),
MedImg(38), No. 10, October 2019, pp. 2303-2313.
IEEE DOI 1910
Manifolds, Storms, Navigation, Magnetic resonance imaging, Estimation, Laplace equations, Cost function, Manifold, magnetic resonance imaging BibRef

Ahmed, A.H., Zhou, R., Yang, Y., Nagpal, P., Salerno, M., Jacob, M.,
Free-Breathing and Ungated Dynamic MRI Using Navigator-Less Spiral SToRM,
MedImg(39), No. 12, December 2020, pp. 3933-3943.
IEEE DOI 2012
Spirals, Navigation, Storms, Heuristic algorithms, Magnetic resonance imaging, Kernel, Image reconstruction, cardiac MRI BibRef

Zhuang, X.H.[Xia-Hai],
Multivariate Mixture Model for Myocardial Segmentation Combining Multi-Source Images,
PAMI(41), No. 12, December 2019, pp. 2933-2946.
IEEE DOI 1911
Myocardium, Image segmentation, Mixture models, Biomedical imaging, Pathology, Magnetic resonance, Multivariate image, multi-modality, cardiac MRI BibRef

Zhuang, X.H.[Xia-Hai], Shi, W.Z.[Wen-Zhe], Duckett, S.G.[Simon G.], Wang, H.Y.[Hai-Yan], Razavi, R.[Reza], Hawkes, D.[David], Rueckert, D.[Daniel], Ourselin, S.[Sebastien],
A Framework Combining Multi-sequence MRI for Fully Automated Quantitative Analysis of Cardiac Global And Regional Functions,
FIMH11(367-374).
Springer DOI 1105
BibRef

Lehnert, J.[Judith], Kolbitsch, C.[Christoph], Wübbeler, G.[Gerd], Chiribiri, A.[Amedeo], Schaeffter, T.[Tobias], Elster, C.[Clemens],
Large-Scale Bayesian Spatial-Temporal Regression with Application to Cardiac MR-Perfusion Imaging,
SIIMS(12), No. 4, 2019, pp. 2035-2062.
DOI Link 1912
BibRef

Rosenzweig, S., Scholand, N., Holme, H.C.M., Uecker, M.,
Cardiac and Respiratory Self-Gating in Radial MRI Using an Adapted Singular Spectrum Analysis (SSA-FARY),
MedImg(39), No. 10, October 2020, pp. 3029-3041.
IEEE DOI 2010
Magnetic resonance imaging, Principal component analysis, Time series analysis, Oscillators, Spectral analysis, Data mining, singular spectrum analysis BibRef

Oksuz, I., Clough, J.R., Ruijsink, B., Anton, E.P., Bustin, A., Cruz, G., Prieto, C., King, A.P., Schnabel, J.A.,
Deep Learning-Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentation,
MedImg(39), No. 12, December 2020, pp. 4001-4010.
IEEE DOI 2012
Image segmentation, Motion segmentation, Biomedical imaging, Image reconstruction, Deep learning, Task analysis, Image quality, image artefacts BibRef

Qi, H., Fuin, N., Cruz, G., Pan, J., Kuestner, T., Bustin, A., Botnar, R.M., Prieto, C.,
Non-Rigid Respiratory Motion Estimation of Whole-Heart Coronary MR Images Using Unsupervised Deep Learning,
MedImg(40), No. 1, January 2021, pp. 444-454.
IEEE DOI 2012
Motion estimation, Image reconstruction, coronary magnetic resonance angiography BibRef

Wang, Z.,
Automatic Localization and Segmentation of the Ventricles in Magnetic Resonance Images,
CirSysVideo(31), No. 2, February 2021, pp. 621-631.
IEEE DOI 2102
Image segmentation, Histograms, Bandwidth, Fitting, Entropy, Deep learning, Slope difference distribution, image segmentation BibRef

Mella, H., Mura, J., Wang, H., Taylor, M.D., Chabiniok, R., Tintera, J., Sotelo, J., Uribe, S.,
HARP-I: A Harmonic Phase Interpolation Method for the Estimation of Motion From Tagged MR Images,
MedImg(40), No. 4, April 2021, pp. 1240-1252.
IEEE DOI 2104
Harmonic analysis, Strain, Heart, Interpolation, Estimation, Biomedical imaging, Cardiac MRI, motion estimation BibRef

Shokina, N.[Nina], Teschner, G.[Gabriel], Bauer, A.[Andreas], Tropea, C.[Cameron], Egger, H.[Herbert], Hennig, J.[Jürgen], Krafft, A.J.[Axel J.],
Parametric Sequential Method for MRI-Based Wall Shear Stress Quantification,
MedImg(40), No. 4, April 2021, pp. 1105-1112.
IEEE DOI 2104
Magnetic resonance imaging, Geometry, Interpolation, Biomedical imaging, Stress, Splines (mathematics), blood flow BibRef

Krebs, J.[Julian], Delingette, H.[Hervé], Ayache, N.[Nicholas], Mansi, T.[Tommaso],
Learning a Generative Motion Model From Image Sequences Based on a Latent Motion Matrix,
MedImg(40), No. 5, May 2021, pp. 1405-1416.
IEEE DOI 2105
Strain, Deformable models, Probabilistic logic, Tracking, Image sequences, Gaussian processes, Data models, Motion model, tracking BibRef

Ammari, A.[Asma], Mahmoudi, R.[Ramzi], Hmida, B.[Badii], Saouli, R.[Rachida], Bedoui, M.H.[Mohamed Hédi],
A review of approaches investigated for right ventricular segmentation using short-axis cardiac MRI,
IET-IPR(15), No. 9, 2021, pp. 1845-1868.
DOI Link 2106
BibRef

Mayer, J.[Johannes], Jin, Y.[Yining], Wurster, T.H.[Thomas-Heinrich], Makowski, M.R.[Marcus R.], Kolbitsch, C.[Christoph],
Evaluation of synergistic image registration for motion-corrected coronary NaF-PET-MR,
Royal(A: 379), No. 2200, June 2021, pp. 20200202.
DOI Link 2107
BibRef

Lyu, Q.[Qing], Shan, H.M.[Hong-Ming], Xie, Y.[Yibin], Kwan, A.C.[Alan C.], Otaki, Y.[Yuka], Kuronuma, K.[Keiichiro], Li, D.[Debiao], Wang, G.[Ge],
Cine Cardiac MRI Motion Artifact Reduction Using a Recurrent Neural Network,
MedImg(40), No. 8, August 2021, pp. 2170-2181.
IEEE DOI 2108
Magnetic resonance imaging, Motion artifacts, Image resolution, Image reconstruction, Feature extraction, Spatial resolution, recurrent neural network BibRef

Hoppe, E.[Elisabeth], Wetzl, J.[Jens], Yoon, S.S.[Seung Su], Bacher, M.[Mario], Roser, P.[Philipp], Stimpel, B.[Bernhard], Preuhs, A.[Alexander], Maier, A.[Andreas],
Deep Learning-Based ECG-Free Cardiac Navigation for Multi-Dimensional and Motion-Resolved Continuous Magnetic Resonance Imaging,
MedImg(40), No. 8, August 2021, pp. 2105-2117.
IEEE DOI 2108
Navigation, Imaging, Image reconstruction, Magnetic resonance imaging, Protocols, Electrocardiography, self-gating BibRef

Koehler, S.[Sven], Hussain, T.[Tarique], Blair, Z.[Zach], Huffaker, T.[Tyler], Ritzmann, F.[Florian], Tandon, A.[Animesh], Pickardt, T.[Thomas], Sarikouch, S.[Samir], Latus, H.[Heiner], Greil, G.[Gerald], Wolf, I.[Ivo], Engelhardt, S.[Sandy],
Unsupervised Domain Adaptation From Axial to Short-Axis Multi-Slice Cardiac MR Images by Incorporating Pretrained Task Networks,
MedImg(40), No. 10, October 2021, pp. 2939-2953.
IEEE DOI 2110
Task analysis, Heart, Image segmentation, Deep learning, Training, competence network for congenital heart defects BibRef

Farzi, M.[Mohsen], Mcclymont, D.[Darryl], Whittington, H.[Hannah], Zdora, M.C.[Marie-Christine], Khazin, L.[Leah], Lygate, C.A.[Craig A.], Rau, C.[Christoph], Dall'Armellina, E.[Erica], Teh, I.[Irvin], Schneider, J.E.[Jürgen E.],
Assessing Myocardial Microstructure With Biophysical Models of Diffusion MRI,
MedImg(40), No. 12, December 2021, pp. 3775-3786.
IEEE DOI 2112
Biological system modeling, Dispersion, Microstructure, Tensors, Extracellular, Standards, Solid modeling, synchrotron X-ray imaging BibRef

Cui, Z.M.[Zhi-Ming], Li, C.J.[Chang-Jian], Du, Z.X.[Zhi-Xu], Chen, N.L.[Neng-Lun], Wei, G.D.[Guo-Dong], Chen, R.N.[Run-Nan], Yang, L.[Lei], Shen, D.G.[Ding-Gang], Wang, W.P.[Wen-Ping],
Structure-Driven Unsupervised Domain Adaptation for Cross-Modality Cardiac Segmentation,
MedImg(40), No. 12, December 2021, pp. 3604-3616.
IEEE DOI 2112
Image segmentation, Feature extraction, Computed tomography, Magnetic resonance imaging, cardiac segmentation BibRef

Du, L.Y.[Lian-Yu], Hu, L.W.[Li-Wei], Zhang, X.Y.[Xiao-Yun], Zhong, Y.M.[Yu-Min], Zhang, Y.[Ya], Wang, Y.F.[Yan-Feng],
Unsupervised Segmentation Framework with Active Contour Models for Cine Cardiac MRI,
ICIP21(56-60)
IEEE DOI 2201
Deep learning, Training, Image segmentation, Annotations, Magnetic resonance imaging, Predictive models, Iterative methods, cine cardiac MRI BibRef

Li, D.P.[Da-Peng], Peng, Y.J.[Yan-Jun], Guo, Y.F.[Yan-Fei], Sun, J.D.[Jin-Dong],
MFAUNet: Multiscale feature attentive U-Net for cardiac MRI structural segmentation,
IET-IPR(16), No. 4, 2022, pp. 1227-1242.
DOI Link 2203
BibRef

Ren, J.C.[Jin-Chang], Sun, H.[He], Zhao, H.M.[Hui-Min], Gao, H.[Hao], Maclellan, C.[Calum], Zhao, S.[Sophia], Luo, X.Y.[Xiao-Yu],
Effective extraction of ventricles and myocardium objects from cardiac magnetic resonance images with a multi-task learning U-Net,
PRL(155), 2022, pp. 165-170.
Elsevier DOI 2203
U-Net, Multi-task learning, Magnetic resonance images (MRI), Ventricles and myocardium extraction, Fusion-based decoder BibRef

Byrne, N.[Nick], Clough, J.R.[James R.], Valverde, I.[Israel], Montana, G.[Giovanni], King, A.P.[Andrew P.],
A Persistent Homology-Based Topological Loss for CNN-Based Multiclass Segmentation of CMR,
MedImg(42), No. 1, January 2023, pp. 3-14.
IEEE DOI 2301
Image segmentation, Topology, Task analysis, Heart, Shape, Feature extraction, CMR, CNN, image segmentation, topology BibRef

Amirrajab, S.[Sina], Al Khalil, Y.[Yasmina], Lorenz, C.[Cristian], Weese, J.[Jürgen], Pluim, J.[Josien], Breeuwer, M.[Marcel],
A Framework for Simulating Cardiac MR Images With Varying Anatomy and Contrast,
MedImg(42), No. 3, March 2023, pp. 726-738.
IEEE DOI 2303
Heart, Data models, Databases, Biological system modeling, Deformable models, Solid modeling, Mathematical models, deep-learning BibRef

Subha, V., Gomathi, G., Boopathi, A.M.[A. Manivanna],
An exploration of ventricle regions segmentation and multiclass disease detection using cardiac MRI,
IJIST(34), No. 1, 2024, pp. e22938.
DOI Link 2401
classification, deep join attention model, deep learning, region integrated deep residual network, ventricle segmentation BibRef

Zhao, X.[Xin], Wang, T.M.[Tong-Ming], Chen, J.S.[Jing-Song], Jiang, B.R.[Bing-Run], Li, H.T.[Hao-Tian], Zhang, N.[Nan], Yang, G.[Guang], Chai, S.[Senchun],
GLRP: Global and local contrastive learning based on relative position for medical image segmentation on cardiac MRI,
IJIST(34), No. 2, 2024, pp. e22992.
DOI Link 2402
contrastive learning, medical image segmentation, relative position BibRef

Cui, H.F.[Heng-Fei], Li, Y.[Yan], Wang, Y.F.[Yi-Fan], Xu, D.[Di], Wu, L.M.[Lian-Ming], Xia, Y.[Yong],
Toward Accurate Cardiac MRI Segmentation With Variational Autoencoder-Based Unsupervised Domain Adaptation,
MedImg(43), No. 8, August 2024, pp. 2924-2936.
IEEE DOI 2408
Feature extraction, Image segmentation, Myocardium, Semantics, Annotations, Image reconstruction, Training, Cardiac segmentation, variational autoencoder BibRef

Zhu, Y.M.[Yue-Ming], Zheng, W.[Wei], Ma, Z.[Zepeng],
Superpixel conditional generation adversarial network for CMR artifact correction,
IVC(149), 2024, pp. 105112.
Elsevier DOI 2408
Cardiac magnetic resonance imaging, Motion artifact removal, Superpixel segmentation, Superpixel pooling BibRef

Xu, R.[Ruru], Oksuz, I.[Ilkay],
Segmentation-aware MRI subsampling for efficient cardiac MRI reconstruction with reinforcement learning,
IVC(150), 2024, pp. 105200.
Elsevier DOI 2409
Cardiac MRI, MRI sub-sampling, Reinforcement learning, Image segmentation, Image reconstruction BibRef

Ye, M.[Meng], Kanski, M.[Mikael], Yang, D.[Dong], Axel, L.[Leon], Metaxas, D.N.[Dimitris N.],
Unsupervised Exemplar-Based Image-to-Image Translation and Cascaded Vision Transformers for Tagged and Untagged Cardiac Cine MRI Registration,
WACV24(7629-7639)
IEEE DOI 2404
Image registration, Deformation, Magnetic resonance imaging, Magnetic resonance, Computer architecture, Coherence, Applications BibRef

Ye, M.[Meng], Yang, D.[Dong], Kanski, M.[Mikael], Axel, L.[Leon], Metaxas, D.N.[Dimitris N.],
Neural Deformable Models for 3D Bi-Ventricular Heart Shape Reconstruction and Modeling from 2D Sparse Cardiac Magnetic Resonance Imaging,
ICCV23(14201-14210)
IEEE DOI 2401
BibRef