A. Madhuranthakam

发表

Comprehensive quantification of signal‐to‐noise ratio and g‐factor for image‐based and k‐space‐based parallel imaging reconstructions

D. Sodickson, C. McKenzie, A. Grant, 2008, Magnetic resonance in medicine.

Multidimensional and Multiresolution Ensemble Networks for Brain Tumor Segmentation

Chandan Ganesh, Sahil Nalawade, Ben Wagner, 2019, bioRxiv.

MRI of the Placenta Accreta Spectrum (PAS) Disorder: Radiomics Analysis Correlates With Surgical and Pathological Outcome

Quyen N. Do, R. Lenkinski, Y. Xi, 2020, Journal of magnetic resonance imaging : JMRI.

Consensus-based technical recommendations for clinical translation of renal ASL MRI

S. Francis, Danny J. J. Wang, D. Alsop, 2019, Magnetic Resonance Materials in Physics, Biology and Medicine.

Volumetric Arterial Spin-labeled Perfusion Imaging of the Kidneys with a Three-dimensional Fast Spin Echo Acquisition.

N. Rofsky, D. Alsop, I. Pedrosa, 2016, Academic radiology.

A Novel Fully Automated Mri-Based Deep Learning Method for Classification of Idh Mutation Status in Brain Gliomas.

J. Maldjian, A. Madhuranthakam, G. Murugesan, 2019, Neuro-oncology.

Time‐resolved 3D contrast‐enhanced MRA of an extended FOV using continuous table motion

S. Riederer, A. Madhuranthakam, J. Glockner, 2004, Magnetic Resonance in Medicine.

Dual‐velocity continuously moving table acquisition for contrast‐enhanced peripheral magnetic resonance angiography

S. Riederer, A. Madhuranthakam, J. Glockner, 2005, Magnetic resonance in medicine.

Contrast-enhanced MR angiography of the peripheral vasculature with a continuously moving table and modified elliptical centric acquisition.

S. Riederer, A. Madhuranthakam, J. Glockner, 2006, Radiology.

Variable field of view for spatial resolution improvement in continuously moving table magnetic resonance imaging

S. Riederer, A. Madhuranthakam, J. Glockner, 2005, Magnetic resonance in medicine.

Improved venous suppression and spatial resolution with SENSE in elliptical centric 3D contrast‐enhanced MR angiography

S. Riederer, A. Madhuranthakam, J. Huston, 2004, Magnetic resonance in medicine.

Changing Paradigms in Breast Cancer Screening: Abbreviated Breast MRI.

A. Madhuranthakam, B. Dogan, A. Mootz, 2019, European journal of breast health.

Robust pCASL perfusion imaging using a 3D Cartesian acquisition with spiral profile reordering (CASPR)

Joshua S. Greer, J. Maldjian, I. Pedrosa, 2019, Magnetic resonance in medicine.

Quantitative Methods in Abdominal MRI: Perfusion Imaging

I. Pedrosa, A. Madhuranthakam, Qing Yuan, 2017, Topics in magnetic resonance imaging : TMRI.

Strategies for reducing respiratory motion artifacts in renal perfusion imaging with arterial spin labeling

Ivan Pedrosa, Weiying Dai, Philip M Robson, 2009, Magnetic resonance in medicine.

Combination of 2D sensitivity encoding and 2D partial fourier techniques for improved acceleration in 3D contrast‐enhanced MR angiography

James F Glockner, Stephen J Riederer, Houchun H Hu, 2006, Magnetic resonance in medicine.

Volumetric fat-water separated T2-weighted MRI

Anja C. S. Brau, Ananth J. Madhuranthakam, Ramesh Venkatesan, 2011, Pediatric Radiology.

MRI-BASED DEEP LEARNING METHOD FOR DETERMINING METHYLATION STATUS OF THE O6-METHYLGUANINE–DNA METHYLTRANSFERASE PROMOTER OUTPERFORMS TISSUE BASED METHODS IN BRAIN GLIOMAS

J. Maldjian, A. Madhuranthakam, G. Murugesan, 2020, bioRxiv.

Automatic segmentation of uterine cavity and placenta on MR images using deep learning

Quyen N. Do, Y. Xi, A. Madhuranthakam, 2022, Medical Imaging.

Magnetic Resonance Imaging Radiomics Analyses for Prediction of High-Grade Histology and Necrosis in Clear Cell Renal Cell Carcinoma: Preliminary Experience.

J. Cadeddu, I. Pedrosa, P. Kapur, 2020, Clinical genitourinary cancer.

Placenta accreta spectrum and hysterectomy prediction using MRI radiomic features

Y. Xi, A. Madhuranthakam, M. Lewis, 2022, Medical Imaging.

Ultrashort echo time MRI of pulmonary water content: assessment in a sponge phantom at 1.5 and 3.0 Tesla.

A. Bankier, R. Lenkinski, A. Madhuranthakam, 2013, Diagnostic and interventional radiology.

Combining inhomogeneous magnetization transfer and multipoint Dixon acquisition: Potential utility and evaluation

R. Lenkinski, D. Alsop, Y. Xi, 2020, Magnetic resonance in medicine.

Whole‐body MRI for metastatic cancer detection using T2‐weighted imaging with fat and fluid suppression

R. Lenkinski, N. Rofsky, I. Pedrosa, 2018, Magnetic resonance in medicine.

Assessment of acute thermal damage volumes in muscle using magnetization‐prepared 3D T2‐weighted imaging following MRI‐guided high‐intensity focused ultrasound therapy

A. Chhabra, Rajiv Chopra, A. Madhuranthakam, 2017, Journal of magnetic resonance imaging : JMRI.

Update on MR imaging of the pulmonary vasculature

P. Rajiah, A. Madhuranthakam, M. Krishnam, 2019, The International Journal of Cardiovascular Imaging.

Intrasession Reliability of Arterial Spin-Labeled MRI–Measured Noncontrast Perfusion in Glioblastoma at 3 T

J. Maldjian, Y. Xi, A. Madhuranthakam, 2020, Tomography.

CEST‐Dixon for human breast lesion characterization at 3 T: A preliminary study

R. Lenkinski, A. Madhuranthakam, J. Keupp, 2018, Magnetic resonance in medicine.

Quantification of Mouse Renal Perfusion Using Arterial Spin Labeled MRI at 1 T.

R. Lenkinski, A. Madhuranthakam, P. Bendel, 2017, Academic radiology.

Statistical clustering of parametric maps from dynamic contrast enhanced MRI and an associated decision tree model for non-invasive tumour grading of T1b solid clear cell renal cell carcinoma

J. Cadeddu, I. Pedrosa, J. Brugarolas, 2017, European Radiology.

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results

Bjoern H Menze, Minh H. Vu, Nisarg A. Shah, 2021, The journal of machine learning for biomedical imaging.

Recent Technical Developments in ASL: A Review of the State of the Art

Joseph G. Woods, Moss Y. Zhao, David L. Thomas, 2022, Magnetic resonance in medicine.

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results pdf

Christos Davatzikos, Gowtham Krishnan Murugesan, Chandan Ganesh, 2021, ArXiv.

A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas

Joseph A. Maldjian, Baowei Fei, Benjamin C. Wagner, 2019, bioRxiv.

A novel fully automated MRI-based deep-learning method for classification of 1p/19q co-deletion status in brain gliomas

Joseph A. Maldjian, Baowei Fei, Chandan Ganesh Bangalore Yogananda, 2020, bioRxiv.

MRI-Based Deep-Learning Method for Determining Glioma MGMT Promoter Methylation Status

J. Maldjian, A. Madhuranthakam, G. Murugesan, 2021, American Journal of Neuroradiology.

Addressing metabolic heterogeneity in clear cell renal cell carcinoma with quantitative Dixon MRI.

R. Deberardinis, J. Cadeddu, R. Lenkinski, 2017, JCI insight.

Modeling Renal Cell Carcinoma in Mice: Bap1 and Pbrm1 Inactivation Drive Tumor Grade.

Quyen N. Do, R. Hammer, I. Pedrosa, 2017, Cancer discovery.

HIF-2 Complex Dissociation, Target Inhibition, and Acquired Resistance with PT2385, a First-in-Class HIF-2 Inhibitor, in Patients with Clear Cell Renal Cell Carcinoma

R. Figlin, I. Pedrosa, J. Brugarolas, 2019, Clinical Cancer Research.

Brain tumor IDH, 1p/19q, and MGMT molecular classification using MRI-based deep learning: an initial study on the effect of motion and motion correction

J. Maldjian, Y. Xi, A. Madhuranthakam, 2022, Journal of medical imaging.

Brain Tumor IDH, 1p/19q, and MGMT Molecular Classification Using MRI-based Deep Learning: Effect of Motion and Motion Correction

Joseph A. Maldjian, Baowei Fei, Benjamin C. Wagner, 2020, bioRxiv.

Classification of brain tumor isocitrate dehydrogenase status using MRI and deep learning

Sahil Nalawade, Ben Wagner, Joseph A Maldjian, 2019, Journal of medical imaging.

Classification of Brain Tumor IDH Status using MRI and Deep Learning

J. Maldjian, A. Madhuranthakam, G. Murugesan, 2019, bioRxiv.

Deciphering Intratumoral Molecular Heterogeneity in Clear Cell Renal Cell Carcinoma with a Radiogenomics Platform

J. Cadeddu, I. Pedrosa, J. Brugarolas, 2021, Clinical Cancer Research.

Magnetic resonance neurography: current perspectives and literature review

A. Chhabra, A. Madhuranthakam, G. Andreisek, 2018, European Radiology.

Tumor Vascularity in Renal Masses: Correlation of Arterial Spin-Labeled and Dynamic Contrast-Enhanced Magnetic Resonance Imaging Assessments.

J. Cadeddu, S. Signoretti, I. Pedrosa, 2016, Clinical genitourinary cancer.

Fully Automated Brain Tumor Segmentation and Survival Prediction of Gliomas using Deep Learning and MRI

Ben Wagner, Joseph A. Maldjian, Baowei Fei, 2019, bioRxiv.

Turbo Spin-Echo Diffusion-Weighted Imaging in Prostate Magnetic Resonance Imaging of Men With Pelvic Hardware.

I. Pedrosa, Y. Xi, A. Madhuranthakam, 2020, Journal of computer assisted tomography.

Quantifying the Impact of Type 2 Diabetes on Brain Perfusion Using Deep Neural Networks

Albert Montillo, Joseph A. Maldjian, Jasmin Divers, 2017, DLMIA/ML-CDS@MICCAI.

Frequency Offset Corrected Inversion Pulse for B0 and B1 Insensitive Fat Suppression at 3T: Application to MR Neurography of Brachial Plexus

Joshua S. Greer, A. Chhabra, A. Madhuranthakam, 2018, Journal of magnetic resonance imaging : JMRI.

MR Neurography of Brachial Plexus at 3.0 T with Robust Fat and Blood Suppression.

A. Chhabra, R. Lenkinski, A. Madhuranthakam, 2017, Radiology.

Texture analysis of magnetic resonance images of the human placenta throughout gestation: A feasibility study

Diane M Twickler, Ananth J Madhuranthakam, Robert E Lenkinski, 2019, PloS one.

The potential role of IDEAL MRI for identification of lipids and hemorrhage in carotid artery plaques.

R. Greenman, A. Madhuranthakam, Xiaoen Wang, 2017, Magnetic resonance imaging.

Update on state‐of‐the‐art for arterial spin labeling (ASL) human perfusion imaging outside of the brain

Erin K. Englund, David L. Thomas, K. Nayak, 2023, Magnetic resonance in medicine.

Intratumor Heterogeneity of Perfusion and Diffusion in Clear-Cell Renal Cell Carcinoma: Correlation With Tumor Cellularity.

J. Cadeddu, S. Signoretti, I. Pedrosa, 2016, Clinical genitourinary cancer.

Multi‐Site Concordance of Diffusion‐Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness

K. Iczkowski, T. Yankeelov, Wei Huang, 2021, Journal of magnetic resonance imaging : JMRI.

Accelerating chemical exchange saturation transfer MRI with parallel blind compressed sensing

Jochen Keupp, Huajun She, Ivan E Dimitrov, 2018, Magnetic resonance in medicine.

Z‐spectrum appearance and interpretation in the presence of fat: Influence of acquisition parameters

R. Lenkinski, A. Madhuranthakam, I. Dimitrov, 2018, Magnetic resonance in medicine.

A Fully Automated Deep Learning Network for Brain Tumor Segmentation

Joseph A. Maldjian, Baowei Fei, Benjamin C. Wagner, 2020, Tomography.

A Deep Learning Pipeline for Automatic Skull Stripping and Brain Segmentation

Joseph A. Maldjian, Chandan Ganesh Bangalore Yogananda, Benjamin C. Wagner, 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

Deep learning-based segmentation of the placenta and uterus on MR images

Baowei Fei, James D. Dormer, Ananth J. Madhuranthakam, 2021, Journal of medical imaging.

Characterizing spatiotemporal information loss in sparse-sampling-based dynamic MRI for monitoring respiration-induced tumor motion in radiotherapy.

Rajiv Chopra, Ivan Pedrosa, Qing Yuan, 2016, Medical physics.

Optimized double inversion recovery for reduction of T1 weighting in fluid‐attenuated inversion recovery

Rohit Bakshi, David C Alsop, Ananth J Madhuranthakam, 2012, Magnetic resonance in medicine.

Added value of diffusion-weighted acquisitions in MRI of the abdomen and pelvis.

I. Pedrosa, A. Madhuranthakam, G. Khatri, 2014, AJR. American journal of roentgenology.

High‐resolution proton density weighted three‐dimensional fast spin echo (3D‐FSE) of the knee with IDEAL at 1.5 tesla: Comparison with 3D‐FSE and 2D‐FSE—initial experience

N. Rofsky, A. Madhuranthakam, M. Hochman, 2012, Journal of magnetic resonance imaging : JMRI.

Assessing reproducibility in magnetic resonance (MR) radiomics features between deep-learning segmented and expert manual segmented data and evaluating their diagnostic performance in pregnant women with suspected placenta accreta spectrum (PAS)

Baowei Fei, Ananth J. Madhuranthakam, Maysam Shahedi, 2021, Medical Imaging.

Segmentation of uterus and placenta in MR images using a fully convolutional neural network

Yin Xi, James D. Dormer, Baowei Fei, 2020, Medical Imaging.

Arterial spin labeled perfusion imaging using three‐dimensional turbo spin echo with a distributed spiral‐in/out trajectory

Michael Schär, Ananth J. Madhuranthakam, James G. Pipe, 2016, Magnetic resonance in medicine.

Undersampled elliptical centric view‐order for improved spatial resolution in contrast‐enhanced MR angiography

James F Glockner, Stephen J Riederer, Houchun H Hu, 2006, Magnetic resonance in medicine.

Current utilities of imaging in grading musculoskeletal soft tissue sarcomas.

Avneesh Chhabra, Ananth J Madhuranthakam, A. Chhabra, 2016, European journal of radiology.

Non-contrast quantitative pulmonary perfusion using flow alternating inversion recovery at 3T: A preliminary study.

Joshua S. Greer, I. Pedrosa, S. Abbara, 2018, Magnetic resonance imaging.

Improved short tau inversion recovery (iSTIR) for increased tumor conspicuity in the abdomen

N. Rofsky, D. Alsop, I. Pedrosa, 2014, Magnetic Resonance Materials in Physics, Biology and Medicine.

Evaluating Multisite rCBV Consistency from DSC-MRI Imaging Protocols and Postprocessing Software Across the NCI Quantitative Imaging Network Sites Using a Digital Reference Object (DRO)

Thomas E. Yankeelov, Chengyue Wu, Mark Muzi, 2019, Tomography.

Numerical equilibration of signal intensity and spatial resolution in time‐resolved continuously moving table imaging

Stephen J Riederer, Houchun H Hu, Ananth J Madhuranthakam, 2006, Magnetic resonance in medicine.

Recovery of phase inconsistencies in continuously moving table extended field of view magnetic resonance imaging acquisitions

Stephen J Riederer, Petrice M Mostardi, Houchun H Hu, 2005, Magnetic resonance in medicine.

Technical Advancements in MR Neurography

R. Lenkinski, A. Madhuranthakam, 2015, Seminars in Musculoskeletal Radiology.

B1‐insensitive fast spin echo using adiabatic square wave enabling of the echo train (SWEET) excitation

David C Alsop, Ananth J Madhuranthakam, Reed F Busse, 2008, Magnetic resonance in medicine.

MRI-Based Deep Learning Method for Classification of IDH Mutation Status

A. Madhuranthakam, B. Wagner, K. Hatanpaa, 2023, Bioengineering.

Single‐shot RARE with Dixon: Application to robust abdominal imaging with uniform fat and water separation at 3T

N. Rofsky, I. Pedrosa, Y. Xi, 2021, Magnetic resonance in medicine.

Brain MR imaging at ultra-low radiofrequency power.

Philip M Robson, David C Alsop, Ananth J Madhuranthakam, 2011, Radiology.

Federated Learning for Brain Tumor Segmentation Using MRI and Transformers

J. Maldjian, A. Madhuranthakam, B. Wagner, 2021, BrainLes@MICCAI.

Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications.

Meher R. Juttukonda, Moss Y. Zhao, M. V. van Osch, 2024, Magnetic Resonance in Medicine.