Comprehensive quantification of signal‐to‐noise ratio and g‐factor for image‐based and k‐space‐based parallel imaging reconstructions
…, AK Grant, AJ Madhuranthakam… - … in Medicine: An …, 2008 - Wiley Online Library
Parallel imaging reconstructions result in spatially varying noise amplification characterized
by the g‐factor, precluding conventional measurements of noise from the final image. A …
by the g‐factor, precluding conventional measurements of noise from the final image. A …
Retracted: A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas
…, TR Patel, B Fei, AJ Madhuranthakam… - Neuro …, 2020 - academic.oup.com
Background. Isocitrate dehydrogenase (IDH) mutation status has emerged as an important
prognostic marker in gliomas. Currently, reliable IDH mutation determination requires …
prognostic marker in gliomas. Currently, reliable IDH mutation determination requires …
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
…, N Singla, A Joyce, H Hill, AJ Madhuranthakam… - Clinical Cancer …, 2020 - AACR
Purpose: The heterodimeric transcription factor HIF-2 is arguably the most important driver
of clear cell renal cell carcinoma (ccRCC). Although considered undruggable, structural …
of clear cell renal cell carcinoma (ccRCC). Although considered undruggable, structural …
Modeling Renal Cell Carcinoma in Mice: Bap1 and Pbrm1 Inactivation Drive Tumor Grade
…, T McKenzie, N Wolff, QN Do, AJ Madhuranthakam… - Cancer discovery, 2017 - AACR
Clear cell renal cell carcinoma (ccRCC) is characterized by BAP1 and PBRM1 mutations,
which are associated with tumors of different grade and prognosis. However, whether BAP1 …
which are associated with tumors of different grade and prognosis. However, whether BAP1 …
Strategies for reducing respiratory motion artifacts in renal perfusion imaging with arterial spin labeling
PM Robson, AJ Madhuranthakam… - … in Medicine: An …, 2009 - Wiley Online Library
Arterial spin labeling (ASL) perfusion measurements may have many applications outside the
brain. In the abdomen, severe image artifacts can arise from motions between acquisitions …
brain. In the abdomen, severe image artifacts can arise from motions between acquisitions …
Magnetic resonance neurography: current perspectives and literature review
A Chhabra, AJ Madhuranthakam, G Andreisek - European radiology, 2018 - Springer
Magnetic resonance neurography (also called MRN or MR neurography) refers to MR imaging
dedicated to the peripheral nerves. It is a technique that enhances selective multiplanar …
dedicated to the peripheral nerves. It is a technique that enhances selective multiplanar …
[HTML][HTML] Consensus-based technical recommendations for clinical translation of renal ASL MRI
…, C Laustsen, A Ljimani, AJ Madhuranthakam… - … Resonance Materials in …, 2020 - Springer
Objectives This study aimed at developing technical recommendations for the acquisition,
processing and analysis of renal ASL data in the human kidney at 1.5 T and 3 T field strengths …
processing and analysis of renal ASL data in the human kidney at 1.5 T and 3 T field strengths …
Recent technical developments in ASL: a review of the state of the art
…, J Guo, AJ Madhuranthakam… - Magnetic resonance …, 2022 - Wiley Online Library
This review article provides an overview of a range of recent technical developments in
advanced arterial spin labeling (ASL) methods that have been developed or adopted by the …
advanced arterial spin labeling (ASL) methods that have been developed or adopted by the …
A fully automated deep learning network for brain tumor segmentation
We developed a fully automated method for brain tumor segmentation using deep learning;
285 brain tumor cases with multiparametric magnetic resonance images from the …
285 brain tumor cases with multiparametric magnetic resonance images from the …
[HTML][HTML] QU-BraTS: MICCAI BraTS 2020 challenge on quantifying uncertainty in brain tumor segmentation-analysis of ranking scores and benchmarking results
…, FY Fang, B Fei, AJ Madhuranthakam… - The journal of …, 2022 - ncbi.nlm.nih.gov
Deep learning (DL) models have provided state-of-the-art performance in various medical
imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) …
imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) …