Gigi Galiana
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Gigi Galiana has a total of 19 co-authors. Here are the top co-authors by number of shared publications:
- Alaa Alashi
Vascular Medicine Outcomes Program (VAMOS), Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
1 shared publication - Albert J. Sinusas
Yale University School of Medicine
1 shared publication - Aseem Vashist
Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT; VA Connecticut Healthcare System, West Haven, CT
1 shared publication - Carlos Mena-Hurtado
Yale School of Medicine
1 shared publication - Christiany Tapia
Vascular Medicine Outcomes Program (VAMOS), Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
1 shared publication - Dana C. Peters
Department of Radiology and Biomedical Imaging Yale University New Haven Connecticut USA
1 shared publication
Latest Publications
- 22 May 2026
- Published by Elsevier in The Journal of Pain
- Vol. 46, 106320
Patients’ pain experience in claudication: Biopsychosocial correlates of frequency, intensity, sleep interference, and chronic pain
- 22 May 2026
- Published by Elsevier in The Journal of Pain
- Vol. 46, 106320
Patients’ pain experience in claudication: Biopsychosocial correlates of frequency, intensity, sleep interference, and chronic pain
- 10 July 2024
- Published by Wiley in Magnetic Resonance in Medicine
- Vol. 92 (6) , 2723-2733
Efficient standardization of clinical T2‐weighted images: Phase‐conjugacy e‐CAMP with projected gradient descent
Purpose: To standardize T‐weighted images from clinical Turbo Spin Echo (TSE) scans by generating corresponding T maps with the goal of removing scanner‐ and/or protocol‐specific heterogeneity.Methods: The T map is estimated by minimizing an objective function containing a data fidelity term in a Virtual Conjugate Coils (VCC) framework, where the signal evolution model is expressed as a linear constraint. The objective function is minimized by Projected Gradient Descent (PGD).Results: The algorithm achieves accuracy comparable to methods with customized sampling schemes for accelerated T mapping. The results are insensitive to the tunable parameters, and the relaxed background phase prior produces better T maps compared to the strict real‐value enforcement. It is worth noting that the algorithm works well with challenging Tw‐TSE data using typical clinical parameters. The observed normalized root mean square error ranges from 6.8% to 12.3% over grey and white matter, a clinically common level of quantitative map error.Conclusion: The novel methodological development creates an efficient algorithm that allows for T map generated from TSE data with typical clinical parameters, such as high resolution, long echo train length, and low echo spacing. Reconstruction of T maps from TSE data with typical clinical parameters has not been previously reported.
- 10 July 2024
- Published by Wiley in Magnetic Resonance in Medicine
- Vol. 92 (6) , 2723-2733
Efficient standardization of clinical T2‐weighted images: Phase‐conjugacy e‐CAMP with projected gradient descent
Purpose: To standardize T‐weighted images from clinical Turbo Spin Echo (TSE) scans by generating corresponding T maps with the goal of removing scanner‐ and/or protocol‐specific heterogeneity.Methods: The T map is estimated by minimizing an objective function containing a data fidelity term in a Virtual Conjugate Coils (VCC) framework, where the signal evolution model is expressed as a linear constraint. The objective function is minimized by Projected Gradient Descent (PGD).Results: The algorithm achieves accuracy comparable to methods with customized sampling schemes for accelerated T mapping. The results are insensitive to the tunable parameters, and the relaxed background phase prior produces better T maps compared to the strict real‐value enforcement. It is worth noting that the algorithm works well with challenging Tw‐TSE data using typical clinical parameters. The observed normalized root mean square error ranges from 6.8% to 12.3% over grey and white matter, a clinically common level of quantitative map error.Conclusion: The novel methodological development creates an efficient algorithm that allows for T map generated from TSE data with typical clinical parameters, such as high resolution, long echo train length, and low echo spacing. Reconstruction of T maps from TSE data with typical clinical parameters has not been previously reported.
- Open Access
- 15 May 2015
- Published by Wiley in Magnetic Resonance in Medicine
- Vol. 75 (4) , 1654-1661
Experimental O‐space turbo spin echo imaging
Purpose: Turbo spin echo (TSE) imaging reduces imaging time by acquiring multiple echoes per repetition (TR), requiring fewer TRs. O‐space can also require fewer TRs by using a combination of nonlinear magnetic gradient fields and surface coil arrays. Although to date, O‐space has only been demonstrated for gradient echo imaging, it is valuable to combine these two techniques. However, collecting multiple O‐space echoes per TR is difficult because of the different local k‐space trajectories and variable T2‐weighting.Theory and Methods: A practical scheme is demonstrated to combine the benefits of TSE and O‐space for highly accelerated T2‐weighted images. The scheme uses a modified acquisition order and filtered projection reconstruction to reduce artifacts caused by T2 decay, while retaining T2 contrast that corresponds to a specific echo time.Results: The experiments revealed that the proposed method can produce highly accelerated T2‐weighted images. Moreover, the method can generate multiple images with different T2 contrasts from a single dataset.Conclusions: The proposed O‐space TSE imaging method requires fewer echoes than conventional TSE and fewer repetitions than conventional O‐space imaging. It retains resilience to undersampling, clearly outperforming Cartesian SENSE at high levels of undersampling, and can generate undistorted images with a range of T2 contrast from a single acquired dataset. Magn Reson Med 75:1654–1661, 2016. © 2015 Wiley Periodicals, Inc.
- 15 May 2015
- Published by Wiley in Magnetic Resonance in Medicine
- Vol. 75 (4) , 1654-1661
Open AccessExperimental O‐space turbo spin echo imaging
Purpose: Turbo spin echo (TSE) imaging reduces imaging time by acquiring multiple echoes per repetition (TR), requiring fewer TRs. O‐space can also require fewer TRs by using a combination of nonlinear magnetic gradient fields and surface coil arrays. Although to date, O‐space has only been demonstrated for gradient echo imaging, it is valuable to combine these two techniques. However, collecting multiple O‐space echoes per TR is difficult because of the different local k‐space trajectories and variable T2‐weighting.Theory and Methods: A practical scheme is demonstrated to combine the benefits of TSE and O‐space for highly accelerated T2‐weighted images. The scheme uses a modified acquisition order and filtered projection reconstruction to reduce artifacts caused by T2 decay, while retaining T2 contrast that corresponds to a specific echo time.Results: The experiments revealed that the proposed method can produce highly accelerated T2‐weighted images. Moreover, the method can generate multiple images with different T2 contrasts from a single dataset.Conclusions: The proposed O‐space TSE imaging method requires fewer echoes than conventional TSE and fewer repetitions than conventional O‐space imaging. It retains resilience to undersampling, clearly outperforming Cartesian SENSE at high levels of undersampling, and can generate undistorted images with a range of T2 contrast from a single acquired dataset. Magn Reson Med 75:1654–1661, 2016. © 2015 Wiley Periodicals, Inc.