Search Results - "Keerthivasan, Mahesh B"

Deep Learning Reconstruction Enables Highly Accelerated Biparametric MR Imaging of the Prostate by Johnson, Patricia M., Tong, Angela, Donthireddy, Awani, Melamud, Kira, Petrocelli, Robert, Smereka, Paul, Qian, Kun, Keerthivasan, Mahesh B., Chandarana, Hersh, Knoll, Florian

“…Background Early diagnosis and treatment of prostate cancer (PCa) can be curative; however, prostate‐specific antigen is a suboptimal screening test for…”
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FastMRI Prostate: A public, biparametric MRI dataset to advance machine learning for prostate cancer imaging by Tibrewala, Radhika, Dutt, Tarun, Tong, Angela, Ginocchio, Luke, Lattanzi, Riccardo, Keerthivasan, Mahesh B., Baete, Steven H., Chopra, Sumit, Lui, Yvonne W., Sodickson, Daniel K., Chandarana, Hersh, Johnson, Patricia M.

“…Magnetic resonance imaging (MRI) has experienced remarkable advancements in the integration of artificial intelligence (AI) for image acquisition and…”
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Editorial for “Microstructural Alterations in Projection and Association Fibers in Neonatal Hypoxia‐Ischemia” by Keerthivasan, Mahesh B.

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Modern Low-Field MRI of the Musculoskeletal System: Practice Considerations, Opportunities, and Challenges by Khodarahmi, Iman, Keerthivasan, Mahesh B., Brinkmann, Inge M., Grodzki, David, Fritz, Jan

“…Magnetic resonance imaging (MRI) provides essential information for diagnosing and treating musculoskeletal disorders. Although most musculoskeletal MRI…”
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Impact of fat on the apparent T1 value of the liver: assessment by water-only derived T1 mapping by Higashi, Mayumi, Tanabe, Masahiro, Yamane, Masatoshi, Keerthivasan, Mahesh B., Imai, Hiroshi, Yonezawa, Teppei, Nakamura, Michihiro, Ito, Katsuyoshi

“…Objectives To determine the impact of fat on the apparent T1 value of the liver using water-only derived T1 mapping. Methods 3-T MRI included 2D Look-Locker T1…”
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Comparison of a Deep Learning-Accelerated vs. Conventional T2-Weighted Sequence in Biparametric MRI of the Prostate by Tong, Angela, Bagga, Barun, Petrocelli, Robert, Smereka, Paul, Vij, Abhinav, Qian, Kun, Grimm, Robert, Kamen, Ali, Keerthivasan, Mahesh B, Nickel, Marcel Dominik, von Busch, Heinrich, Chandarana, Hersh

“…Demand for prostate MRI is increasing, but scan times remain long even in abbreviated biparametric MRIs (bpMRI). Deep learning can be leveraged to accelerate…”
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Fat Suppression in Distal Extremity 3-T MRI Using Spectral Heterogeneity Adaptive Radiofrequency Pulses by Khodarahmi, Iman, Walter, William R, Bruno, Mary, Brinkmann, Inge M, Keerthivasan, Mahesh B, Chebrolu, Venkata V, Fritz, Jan

“…Background Conventional chemical shift selective (CHESS) fat suppression may fail in distal extremity MRI due to sensitivity to field inhomogeneities. Purpose…”
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MR electrical properties mapping using vision transformers and canny edge detectors by Giannakopoulos, Ilias I, Carluccio, Giuseppe, Keerthivasan, Mahesh B, Koerzdoerfer, Gregor, Lakshmanan, Karthik, De Moura, Hector L, Cruz Serrallés, José E, Lattanzi, Riccardo

“…We developed a 3D vision transformer-based neural network to reconstruct electrical properties (EP) from magnetic resonance measurements. Our network uses the…”
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Performance of MR learned pulse sequences for 3D bi-exponential, stretched-exponential, and mono-exponential T2 and T1ρ mapping of knee cartilage by Zibetti, Marcelo V W, De Moura, Hector L, Monga, Anmol, Keerthivasan, Mahesh B, Regatte, Ravinder R

“…To compare the performance of a learned magnetization-prepared gradient echo (L-MPGRE) sequence against a commonly used sequence for 3D T2 and T1ρ mapping of…”
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Performance of MR learned pulse sequences for 3D bi-exponential, stretched-exponential, and mono-exponential T 2 and T 1ρ mapping of knee cartilage by Zibetti, Marcelo V W, De Moura, Hector L, Monga, Anmol, Keerthivasan, Mahesh B, Regatte, Ravinder R

“…To compare the performance of a learned magnetization-prepared gradient echo (L-MPGRE) sequence against a commonly used sequence for 3D T and T mapping of the…”
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New-Generation Low-Field Magnetic Resonance Imaging of Hip Arthroplasty Implants Using Slice Encoding for Metal Artifact Correction: First In Vitro Experience at 0.55 T and Comparison With 1.5 T by Khodarahmi, Iman, Brinkmann, Inge M., Lin, Dana J., Bruno, Mary, Johnson, Patricia M., Knoll, Florian, Keerthivasan, Mahesh B., Chandarana, Hersh, Fritz, Jan

“…Despite significant progress, artifact-free visualization of the bone and soft tissues around hip arthroplasty implants remains an unmet clinical need…”
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Low-field 0.55 T MRI for assessment of pulmonary groundglass and fibrosis-like opacities: Inter-reader and inter-modality concordance by Azour, Lea, Condos, Rany, Keerthivasan, Mahesh B., Bruno, Mary, Pandit Sood, Terlika, Landini, Nicholas, Silverglate, Quinn, Babb, James, Chandarana, Hersh, Moore, William H.

“…•Inter-reader agreement was lower for MRI than CT.•Low-field MRI had moderate concordance with CT for detection of groundglass opacities.•Inter-modality…”
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Optimizing variable flip angles in magnetization‐prepared gradient‐echo sequences for efficient 3D‐T1ρ mapping by Zibetti, Marcelo V. W., De Moura, Hector L., Keerthivasan, Mahesh B., Regatte, Ravinder R.

“…Purpose To optimize the choice of the flip angles of magnetization‐prepared gradient‐echo sequences for improved accuracy, precision, and speed of 3D‐T1ρ…”
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Feasibility of 3D MRI fingerprinting for rapid knee cartilage T1, T2, and T1ρ mapping at 0.55T: Comparison with 3T by De Moura, Hector L., Monga, Anmol, Zhang, Xiaoxia, Zibetti, Marcelo V. W., Keerthivasan, Mahesh B., Regatte, Ravinder R.

“…Low‐field strength scanners present an opportunity for more inclusive imaging exams and bring several challenges including lower signal‐to‐noise ratio (SNR)…”
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Accelerated MR parameter mapping with a union of local subspaces constraint by Mandava, Sagar, Keerthivasan, Mahesh B., Li, Zhitao, Martin, Diego R., Altbach, Maria I., Bilgin, Ali

“…Purpose A new reconstruction method for multi‐contrast imaging and parameter mapping based on a union of local subspaces constraint is presented. Theory…”
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Abdominal T2‐Weighted Imaging and T2 Mapping Using a Variable Flip Angle Radial Turbo Spin‐Echo Technique by Keerthivasan, Mahesh B., Galons, Jean‐Philippe, Johnson, Kevin, Umapathy, Lavanya, Martin, Diego R., Bilgin, Ali, Altbach, Maria I.

“…Background T2 mapping is of great interest in abdominal imaging but current methods are limited by low resolution, slice coverage, motion sensitivity, or…”
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Improving subspace constrained radial fast spin echo MRI using block matching driven non-local low rank regularization by Mandava, Sagar, Keerthivasan, Mahesh B, Martin, Diego R, Altbach, Maria I, Bilgin, Ali

“…Subspace-constrained reconstruction methods restrict the relaxation signals (of size M) in the scene to a pre-determined subspace (of size K≪M) and allow…”
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Radial streak artifact reduction using phased array beamforming by Mandava, Sagar, Keerthivasan, Mahesh B., Martin, Diego R., Altbach, Maria I., Bilgin, Ali

“…Purpose A new method for streak artifact reduction in radial MRI based on phased array filtering. Theory Radial imaging in applications that require large…”
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A multi-scale residual network for accelerated radial MR parameter mapping by Fu, Zhiyang, Mandava, Sagar, Keerthivasan, Mahesh B., Li, Zhitao, Johnson, Kevin, Martin, Diego R., Altbach, Maria I., Bilgin, Ali

“…A deep learning MR parameter mapping framework which combines accelerated radial data acquisition with a multi-scale residual network (MS-ResNet) for image…”
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Automated thalamic nuclei segmentation using multi-planar cascaded convolutional neural networks by Majdi, Mohammad S., Keerthivasan, Mahesh B., Rutt, Brian K., Zahr, Natalie M., Rodriguez, Jeffrey J., Saranathan, Manojkumar

“…To develop a fast and accurate convolutional neural network based method for segmentation of thalamic nuclei. A cascaded multi-planar scheme with a modified…”
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