World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
5280
World Ranking
10351
National Ranking
4335

Overview

Ali Gholipour is affiliated with Harvard University in the United States and works primarily within the field of Medicine. Their research focuses extensively on Radiology, Nuclear Medicine and Imaging, as well as Pediatrics, Perinatology and Child Health. Additional attention is given to Computer Vision and Pattern Recognition, Artificial Intelligence, and Cognitive Neuroscience within their body of work.

The main topics of research covered by Ali Gholipour include:

  • Fetal and Pediatric Neurological Disorders
  • Advanced Neuroimaging Techniques and Applications
  • Advanced MRI Techniques and Applications
  • Neonatal and fetal brain pathology
  • MRI in cancer diagnosis
  • Domain Adaptation and Few-Shot Learning
  • Functional Brain Connectivity Studies

The scientist has been involved in numerous publications, with some of the noteworthy recent papers including:

  • Brain charts for the human lifespan, 2022, Nature
  • Transfer learning in medical image segmentation: New insights from analysis of the dynamics of model parameters and learned representations, 2021, Artificial Intelligence in Medicine
  • Regional Brain Growth Trajectories in Fetuses with Congenital Heart Disease, 2020, Annals of Neurology
  • A Deep Attentive Convolutional Neural Network for Automatic Cortical Plate Segmentation in Fetal MRI, 2020, IEEE Transactions on Medical Imaging
  • Tuber Locations Associated with Infantile Spasms Map to a Common Brain Network, 2021, Annals of Neurology

Ali Gholipour frequently collaborates with several co-authors, including Simon K. Warfield, Davood Karimi, Onur Afacan, and Clemente Velasco-Annis. These partnerships have contributed to advancing research in their fields of study.

Their publications have appeared repeatedly in venues such as:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
  • Human Brain Mapping
  • Cerebral Cortex

Best Publications

  • Tversky loss function for image segmentation using 3D fully convolutional deep networks

    Seyed Sadegh Mohseni Salehi;Seyed Sadegh Mohseni Salehi;Deniz Erdogmus;Ali Gholipour

  • Deep learning with noisy labels: exploring techniques and remedies in medical image analysis

    Davood Karimi;Haoran Dou;Simon K. Warfield;Ali Gholipour

  • Robust Super-Resolution Volume Reconstruction From Slice Acquisitions: Application to Fetal Brain MRI

    A Gholipour;J A Estroff;S K Warfield

  • Brain Functional Localization: A Survey of Image Registration Techniques

    A. Gholipour;N. Kehtarnavaz;R. Briggs;M. Devous

  • A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth

    Ali Gholipour;Caitlin K. Rollins;Clemente Velasco-Annis;Abdelhakim Ouaalam

  • Auto-Context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging

    Seyed Sadegh Mohseni Salehi;Deniz Erdogmus;Ali Gholipour

  • Asymmetric Loss Functions and Deep Densely Connected Networks for Highly Imbalanced Medical Image Segmentation: Application to Multiple Sclerosis Lesion Detection

    Seyed Raein Hashemi;Seyed Sadegh Mohseni Salehi;Deniz Erdogmus;Sanjay P. Prabhu

  • Predicting Chaotic Time Series Using Neural and Neurofuzzy Models: A Comparative Study

    Ali Gholipour;Babak N. Araabi;Caro Lucas

  • Super-resolution reconstruction to increase the spatial resolution of diffusion weighted images from orthogonal anisotropic acquisitions

    Benoit Scherrer;Ali Gholipour;Simon K. Warfield

  • Tversky loss function for image segmentation using 3D fully convolutional deep networks

    Seyed Sadegh Mohseni Salehi;Seyed Sadegh Mohseni Salehi;Deniz Erdogmus;Ali Gholipour

  • Fetal brain growth portrayed by a spatiotemporal diffusion tensor MRI atlas computed from in utero images.

    Shadab Khan;Lana Vasung;Bahram Marami;Caitlin K. Rollins

  • Transfer learning in medical image segmentation: New insights from analysis of the dynamics of model parameters and learned representations.

    Davood Karimi;Simon K. Warfield;Ali Gholipour

  • Real-Time Deep Pose Estimation With Geodesic Loss for Image-to-Template Rigid Registration

    Seyed Sadegh Mohseni Salehi;Shadab Khan;Deniz Erdogmus;Ali Gholipour

  • Fetal brain volumetry through MRI volumetric reconstruction and segmentation.

    Ali Gholipour;Judy A. Estroff;Carol E. Barnewolt;Susan A. Connolly

  • Super-resolution reconstruction of single anisotropic 3D MR images using residual convolutional neural network

    Jinglong Du;Zhongshi He;Lulu Wang;Ali Gholipour

  • Multi-Atlas Multi-Shape Segmentation of Fetal Brain MRI for Volumetric and Morphometric Analysis of Ventriculomegaly

    Ali Gholipour;Alireza Akhondi-Asl;Judy A. Estroff;Simon K. Warfield

  • Convolution-Free Medical Image Segmentation Using Transformers

    Davood Karimi;Serge Didenko Vasylechko;Ali Gholipour

  • Semi Supervised Learning with Deep Embedded Clustering for Image Classification and Segmentation.

    Joseph Enguehard;Peter O'Halloran;Ali Gholipour

  • Temporal Slice Registration and Robust Diffusion-Tensor Reconstruction for Improved Fetal Brain Structural Connectivity Analysis

    Bahram Marami;Seyed Sadegh Mohseni Salehi;Onur Afacan;Benoit Scherrer

  • A Deep Attentive Convolutional Neural Network for Automatic Cortical Plate Segmentation in Fetal MRI

    Haoran Dou;Davood Karimi;Caitlin K. Rollins;Cynthia M. Ortinau

  • Solar activity forecast: Spectral analysis and neurofuzzy prediction

    Ali Gholipour;Caro Lucas;Babak N. Araabi;Masoud Shafiee

  • Fetal brain tissue annotation and segmentation challenge results

    Unknown

  • Real-time automatic fetal brain extraction in fetal MRI by deep learning

    Seyed Sadegh Mohseni Salehi;Seyed Raein Hashemi;Clemente Velasco-Annis;Abdelhakim Ouaalam

  • Real-Time Automatic Fetal Brain Extraction in Fetal MRI by Deep Learning

    Seyed Sadegh Mohseni Salehi;Seyed Raein Hashemi;Clemente Velasco-Annis;Abdelhakim Ouaalam

Frequent Co-Authors

Simon K. Warfield
Simon K. Warfield Boston Children's Hospital
Nasser Kehtarnavaz
Nasser Kehtarnavaz The University of Texas at Dallas
Deniz Erdogmus
Deniz Erdogmus Northeastern University
Jane W. Newburger
Jane W. Newburger Boston Children's Hospital
Caro Lucas
Caro Lucas University of Tehran
Babak Nadjar Araabi
Babak Nadjar Araabi University of Tehran
P. Ellen Grant
P. Ellen Grant Boston Children's Hospital
Mustafa Sahin
Mustafa Sahin Boston Children's Hospital
Catherine Limperopoulos
Catherine Limperopoulos George Washington University
Alan C. Evans
Alan C. Evans McGill University

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