Accelerating cardiac diffusion tensor imaging combining local low-rank and 3D TV constraint
| العنوان: | Accelerating cardiac diffusion tensor imaging combining local low-rank and 3D TV constraint |
|---|---|
| المؤلفون: | Jianping Huang, Wanyu Liu, Lihui Wang, Chun-Yu Chu, Yuemin Zhu |
| المساهمون: | Imagerie et modélisation Vasculaires, Thoraciques et Cérébrales (MOTIVATE), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM) |
| المصدر: | HAL Magnetic Resonance Materials in Physics, Biology and Medicine Magnetic Resonance Materials in Physics, Biology and Medicine, Springer Verlag, 2019, 32 (4), pp.407-422. ⟨10.1007/s10334-019-00747-1⟩ |
| مصطلحات موضوعية: | Time Factors, Rank (linear algebra), Computer science, Biophysics, Iterative reconstruction, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Matrix (mathematics), ：Cardiac Diffusion Tensor Imaging, 0302 clinical medicine, Imaging, Three-Dimensional, Fractional anisotropy, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Image Processing, Computer-Assisted, Humans, Radiology, Nuclear Medicine and imaging, Radiological and Ultrasound Technology, Helix angle, Block matrix, Heart, Locally low-rank regularization, Image Enhancement, Compressed sensing, Diffusion Tensor Imaging, Anisotropy, Constrained reconstruction, Algorithm, Algorithms, Software, Diffusion MRI, Sparse sampling |
| الوصف: | International audience; Object: Diffusion tensor magnetic resonance imaging (DT-MRI, or DTI) is a promising technique for invasively probing biological tissue structures. However, DTI is known to suffer from much longer acquisition time with respect to conventional MRI and the problem is worsened when dealing with in vivo acquisitions. Therefore, faster DTI for both ex vivo and in vivo scans is highly desired. Materials and Methods: This paper proposes a new compressed sensing (CS) reconstruction method that employs local low-rank (LLR) model and three-dimensional (3D) total variation (TV) constraint to reconstruct cardiac diffusion-weighted (DW) images from highly undersampled k-space data. The LLR model takes the set of DW images corresponding to different diffusion gradient directions as a 3D image volume and decomposes the latter into overlapping 3D blocks. Then, the 3D blocks are stacked as two-dimensional (2D) matrix. Finally, low-rank property is applied to each block matrix and the 3D TV constraint to the 3D image volume. The underlying constrained optimization problem is finally solved using the first-order fast method. The proposed method is evaluated on real ex vivo cardiac DTI data as a prerequisite to in vivo cardiac DTI applications. Results: The results on real human ex vivo cardiac DTI images demonstrate that the proposed method exhibits lower reconstruction errors for DTI indices, including fractional anisotropy (FA), mean diffusivities (MD), transverse angle (TA) and helix angle (HA), compared to existing CS-based DTI image reconstruction techniques. Conclusion: The proposed method provides better reconstruction quality and more accurate DTI indices in comparison with the state-of-the-art CS-based DW image reconstruction methods. |
| تدمد: | 0968-5243 1352-8661 |
| DOI: | 10.1007/s10334-019-00747-1⟩ |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::141f5673303db2a68a6159fee0b0620a https://hal.archives-ouvertes.fr/hal-02073170 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....141f5673303db2a68a6159fee0b0620a |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 09685243 13528661 |
|---|---|
| DOI: | 10.1007/s10334-019-00747-1⟩ |