Polina Golland

About

Polina Golland is a professor at MIT CSAIL, affiliated with the Department of Electrical Engineering and Computer Science. Her research areas include AI for Healthcare and Life Sciences, Artificial Intelligence and Machine Learning, and Biological and Medical Devices and Systems. She focuses on developing techniques for analysis and synthesis of systems that interact with the external world through perception, communication, and action, while also learning, making decisions, and adapting to changing environments. Her work leverages computational, theoretical, and experimental tools to advance sensors, energy transducers, physical substrates for computation, and systems addressing shared human challenges.

Research topics

• Medicine
• Radiology
• Biology
• Internal medicine
• Cardiology

Selected publications

• SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry

  Science Advances · 2023-02-01 · 193 citations

  articleOpen access

  Every year, millions of brain magnetic resonance imaging (MRI) scans are acquired in hospitals across the world. These have the potential to revolutionize our understanding of many neurological diseases, but their morphometric analysis has not yet been possible due to their anisotropic resolution. We present an artificial intelligence technique, “SynthSR,” that takes clinical brain MRI scans with any MR contrast (T1, T2, etc.), orientation (axial/coronal/sagittal), and resolution and turns them…

  PublisherDOI

• Cognitive Impairment and Dementia After Stroke: Design and Rationale for the DISCOVERY Study

  Stroke · 2021-05-27 · 122 citations

  reviewOpen access

  Stroke is a leading cause of the adult disability epidemic in the United States, with a major contribution from poststroke cognitive impairment and dementia (PSCID), the rates of which are disproportionally high among the health disparity populations. Despite the PSCID's overwhelming impact on public health, a knowledge gap exists with regard to the complex interaction between the acute stroke event and highly prevalent preexisting brain pathology related to cerebrovascular and Alzheimer disease…

  PublisherOA PDFDOI

• Placental MRI: Effect of maternal position and uterine contractions on placental BOLD MRI measurements

  Placenta · 2020 · 50 citations

  DOI

• Deep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imaging

  NeuroImage · 2025-02-01 · 1 citations

  articleOpen access

  Altered neurometabolism is an important pathological mechanism in many neurological diseases and brain cancer, which can be mapped non-invasively by Magnetic Resonance Spectroscopic Imaging (MRSI). Advanced MRSI using non-cartesian compressed-sense acquisition enables fast high-resolution metabolic imaging but has lengthy reconstruction times that limits throughput and needs expert user interaction. Here, we present a robust and efficient Deep Learning reconstruction embedded in a physical model…

  PublisherDOI

• Fast Multi-Stack Slice-to-Volume Reconstruction via Multi-Scale Unrolled Optimization

  arXiv (Cornell University) · 2026-01-12

  preprintOpen accessSenior author

  Fully convolutional networks have become the backbone of modern medical imaging due to their ability to learn multi-scale representations and perform end-to-end inference. Yet their potential for slice-to-volume reconstruction (SVR), the task of jointly estimating 3D anatomy and slice poses from misaligned 2D acquisitions, remains underexplored. We introduce a fast convolutional framework that fuses multiple orthogonal 2D slice stacks to recover coherent 3D structure and refines slice alignment…

  PublisherDOI

Recent grants

• Finding Structure in the Space of Activation Profiles in fMRI

  NSF · $850k · 2009–2013

• CAREER: Computational Modeling of Spatial Activation Patterns in fMRI

  NSF · $500k · 2007–2013

• Neuroimaging Analysis Center (NAC)

  NIH · $27.7M · 1998–2024

Frequent coauthors

• Adrian V. Dalca

  207 shared

• Anne‐Katrin Giese

  Massachusetts General Hospital

  195 shared

• Juan Eugenio Iglesias

  Harvard University

  161 shared

• Natalia S. Rost

  Massachusetts General Hospital

  115 shared

• Markus D. Schirmer

  German Center for Neurodegenerative Diseases

  115 shared

• Elfar Adalsteinsson

  110 shared

• Ona Wu

  Athinoula A. Martinos Center for Biomedical Imaging

  107 shared

• Jordi Jiménez-Conde

  Hospital Del Mar

  101 shared

Labs

• MIT EECS Artificial Intelligence + Decision-makingPI

Similar researchers at Massachusetts Institute of Technology

• Manolis Kellish-164
• Antonio Torralbah-133
• Daniela Rush-129