Search Results for author: Juan Eugenio Iglesias

Found 41 papers, 19 papers with code

Fully Convolutional Slice-to-Volume Reconstruction for Single-Stack MRI

no code implementations5 Dec 2023 Sean I. Young, Yaël Balbastre, Bruce Fischl, Polina Golland, Juan Eugenio Iglesias

Here, we propose a SVR method that overcomes the shortcomings of previous work and produces state-of-the-art reconstructions in the presence of extreme inter-slice motion.

3D Reconstruction Depth Estimation +1

Brain-ID: Learning Robust Feature Representations for Brain Imaging

1 code implementation28 Nov 2023 Peirong Liu, Oula Puonti, Xiaoling Hu, Daniel C. Alexander, Juan Eugenio Iglesias

Recent learning-based approaches have made astonishing advances in calibrated medical imaging like computerized tomography, yet they struggle to generalize in uncalibrated modalities -- notoriously magnetic resonance imaging (MRI), where performance is highly sensitive to the differences in MR contrast, resolution, and orientation between the training and testing data.

Anatomy Brain Segmentation +2

USLR: an open-source tool for unbiased and smooth longitudinal registration of brain MR

1 code implementation14 Nov 2023 Adrià Casamitjana, Roser Sala-Llonch, Karim Lekadir, Juan Eugenio Iglesias

We present USLR, a computational framework for longitudinal registration of brain MRI scans to estimate nonlinear image trajectories that are smooth across time, unbiased to any timepoint, and robust to imaging artefacts.

Bayesian Inference Image Segmentation +2

Robust and Generalisable Segmentation of Subtle Epilepsy-causing Lesions: a Graph Convolutional Approach

1 code implementation2 Jun 2023 Hannah Spitzer, Mathilde Ripart, Abdulah Fawaz, Logan Z. J. Williams, MELD project, Emma Robinson, Juan Eugenio Iglesias, Sophie Adler, Konrad Wagstyl

On a multi-centre dataset of 1015 participants with surface-based features and manual lesion masks from structural MRI data, the proposed GCN achieved an AUC of 0. 74, a significant improvement against a previously used vertex-wise multi-layer perceptron (MLP) classifier (AUC 0. 64).

Lesion Detection Semantic Segmentation +1

The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI

no code implementations1 Jun 2023 Ahmed W. Moawad, Anastasia Janas, Ujjwal Baid, Divya Ramakrishnan, Leon Jekel, Kiril Krantchev, Harrison Moy, Rachit Saluja, Klara Osenberg, Klara Wilms, Manpreet Kaur, Arman Avesta, Gabriel Cassinelli Pedersen, Nazanin Maleki, Mahdi Salimi, Sarah Merkaj, Marc von Reppert, Niklas Tillmans, Jan Lost, Khaled Bousabarah, Wolfgang Holler, MingDe Lin, Malte Westerhoff, Ryan Maresca, Katherine E. Link, Nourel Hoda Tahon, Daniel Marcus, Aristeidis Sotiras, Pamela Lamontagne, Strajit Chakrabarty, Oleg Teytelboym, Ayda Youssef, Ayaman Nada, Yuri S. Velichko, Nicolo Gennaro, Connectome Students, Group of Annotators, Justin Cramer, Derek R. Johnson, Benjamin Y. M. Kwan, Boyan Petrovic, Satya N. Patro, Lei Wu, Tiffany So, Gerry Thompson, Anthony Kam, Gloria Guzman Perez-Carrillo, Neil Lall, Group of Approvers, Jake Albrecht, Udunna Anazodo, Marius George Lingaru, Bjoern H Menze, Benedikt Wiestler, Maruf Adewole, Syed Muhammad Anwar, Dominic LaBella, Hongwei Bran Li, Juan Eugenio Iglesias, Keyvan Farahani, James Eddy, Timothy Bergquist, Verena Chung, Russel Takeshi Shinohara, Farouk Dako, Walter Wiggins, Zachary Reitman, Chunhao Wang, Xinyang Liu, Zhifan Jiang, Koen van Leemput, Marie Piraud, Ivan Ezhov, Elaine Johanson, Zeke Meier, Ariana Familiar, Anahita Fathi Kazerooni, Florian Kofler, Evan Calabrese, Sanjay Aneja, Veronica Chiang, Ichiro Ikuta, Umber Shafique, Fatima Memon, Gian Marco Conte, Spyridon Bakas, Jeffrey Rudie, Mariam Aboian

Clinical monitoring of metastatic disease to the brain can be a laborious and time-consuming process, especially in cases involving multiple metastases when the assessment is performed manually.

Brain Tumor Segmentation Decision Making +2

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

no code implementations26 May 2023 Anahita Fathi Kazerooni, Nastaran Khalili, Xinyang Liu, Debanjan Haldar, Zhifan Jiang, Syed Muhammed Anwar, Jake Albrecht, Maruf Adewole, Udunna Anazodo, Hannah Anderson, Sina Bagheri, Ujjwal Baid, Timothy Bergquist, Austin J. Borja, Evan Calabrese, Verena Chung, Gian-Marco Conte, Farouk Dako, James Eddy, Ivan Ezhov, Ariana Familiar, Keyvan Farahani, Shuvanjan Haldar, Juan Eugenio Iglesias, Anastasia Janas, Elaine Johansen, Blaise V Jones, Florian Kofler, Dominic LaBella, Hollie Anne Lai, Koen van Leemput, Hongwei Bran Li, Nazanin Maleki, Aaron S McAllister, Zeke Meier, Bjoern Menze, Ahmed W Moawad, Khanak K Nandolia, Julija Pavaine, Marie Piraud, Tina Poussaint, Sanjay P Prabhu, Zachary Reitman, Andres Rodriguez, Jeffrey D Rudie, Ibraheem Salman Shaikh, Lubdha M. Shah, Nakul Sheth, Russel Taki Shinohara, Wenxin Tu, Karthik Viswanathan, Chunhao Wang, Jeffrey B Ware, Benedikt Wiestler, Walter Wiggins, Anna Zapaishchykova, Mariam Aboian, Miriam Bornhorst, Peter de Blank, Michelle Deutsch, Maryam Fouladi, Lindsey Hoffman, Benjamin Kann, Margot Lazow, Leonie Mikael, Ali Nabavizadeh, Roger Packer, Adam Resnick, Brian Rood, Arastoo Vossough, Spyridon Bakas, Marius George Linguraru

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children.

Benchmarking Brain Tumor Segmentation +2

Domain-agnostic segmentation of thalamic nuclei from joint structural and diffusion MRI

no code implementations5 May 2023 Henry F. J. Tregidgo, Sonja Soskic, Mark D. Olchanyi, Juri Althonayan, Benjamin Billot, Chiara Maffei, Polina Golland, Anastasia Yendiki, Daniel C. Alexander, Martina Bocchetta, Jonathan D. Rohrer, Juan Eugenio Iglesias

Some tools have attempted to incorporate information from diffusion MRI in the segmentation to refine these boundaries, but do not generalise well across diffusion MRI acquisitions.

Cortical analysis of heterogeneous clinical brain MRI scans for large-scale neuroimaging studies

no code implementations2 May 2023 Karthik Gopinath, Douglas N. Greve, Sudeshna Das, Steve Arnold, Colin Magdamo, Juan Eugenio Iglesias

Here we present the first method for cortical reconstruction, registration, parcellation, and thickness estimation for clinical brain MRI scans of any resolution and pulse sequence.

3D Reconstruction

A Domain-specific Perceptual Metric via Contrastive Self-supervised Representation: Applications on Natural and Medical Images

no code implementations3 Dec 2022 Hongwei Bran Li, Chinmay Prabhakar, Suprosanna Shit, Johannes Paetzold, Tamaz Amiranashvili, JianGuo Zhang, Daniel Rueckert, Juan Eugenio Iglesias, Benedikt Wiestler, Bjoern Menze

We find that in the natural image domain, CSR behaves on par with the supervised one on several perceptual tests as a metric, and in the medical domain, CSR better quantifies perceptual similarity concerning the experts' ratings.

Image Generation

SVoRT: Iterative Transformer for Slice-to-Volume Registration in Fetal Brain MRI

1 code implementation22 Jun 2022 Junshen Xu, Daniel Moyer, P. Ellen Grant, Polina Golland, Juan Eugenio Iglesias, Elfar Adalsteinsson

Experiments with real-world MRI data are also performed to demonstrate the ability of the proposed model to improve the quality of 3D reconstruction under severe fetal motion.

3D Reconstruction

SuperWarp: Supervised Learning and Warping on U-Net for Invariant Subvoxel-Precise Registration

no code implementations15 May 2022 Sean I. Young, Yaël Balbastre, Adrian V. Dalca, William M. Wells, Juan Eugenio Iglesias, Bruce Fischl

In recent years, learning-based image registration methods have gradually moved away from direct supervision with target warps to instead use self-supervision, with excellent results in several registration benchmarks.

Image Registration

Accurate super-resolution low-field brain MRI

no code implementations7 Feb 2022 Juan Eugenio Iglesias, Riana Schleicher, Sonia Laguna, Benjamin Billot, Pamela Schaefer, Brenna McKaig, Joshua N. Goldstein, Kevin N. Sheth, Matthew S. Rosen, W. Taylor Kimberly

To address this challenge, recent advances in machine learning facilitate the synthesis of higher resolution images derived from one or multiple lower resolution scans.

Image Enhancement Super-Resolution

Supervision by Denoising

no code implementations7 Feb 2022 Sean I. Young, Adrian V. Dalca, Enzo Ferrante, Polina Golland, Christopher A. Metzler, Bruce Fischl, Juan Eugenio Iglesias

SUD unifies stochastic averaging and spatial denoising techniques under a spatio-temporal denoising framework and alternates denoising and model weight update steps in an optimization framework for semi-supervision.

Denoising Image Reconstruction +3

Synth-by-Reg (SbR): Contrastive learning for synthesis-based registration of paired images

1 code implementation30 Jul 2021 Adrià Casamitjana, Matteo Mancini, Juan Eugenio Iglesias

Nonlinear inter-modality registration is often challenging due to the lack of objective functions that are good proxies for alignment.

Contrastive Learning Translation

Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlas

1 code implementation30 Apr 2021 Adrià Casamitjana, Marco Lorenzi, Sebastiano Ferraris, Loc Peter, Marc Modat, Allison Stevens, Bruce Fischl, Tom Vercauteren, Juan Eugenio Iglesias

The model relies on a spanning tree of latent transforms connecting all the sections and slices of the reference volume, and assumes that the registration between any pair of images can be see as a noisy version of the composition of (possibly inverted) latent transforms connecting the two images.

3D Reconstruction Bayesian Inference

Active Annotation of Informative Overlapping Frames in Video Mosaicking Applications

1 code implementation30 Dec 2020 Loic Peter, Marcel Tella-Amo, Dzhoshkun Ismail Shakir, Jan Deprest, Sebastien Ourselin, Juan Eugenio Iglesias, Tom Vercauteren

In addition to the efficient construction of a mosaic, our framework provides, as a by-product, ground truth landmark correspondences which can be used for evaluation or learning purposes.

Joint super-resolution and synthesis of 1 mm isotropic MP-RAGE volumes from clinical MRI exams with scans of different orientation, resolution and contrast

1 code implementation24 Dec 2020 Juan Eugenio Iglesias, Benjamin Billot, Yael Balbastre, Azadeh Tabari, John Conklin, Daniel C. Alexander, Polina Golland, Brian L. Edlow, Bruce Fischl

Most existing algorithms for automatic 3D morphometry of human brain MRI scans are designed for data with near-isotropic voxels at approximately 1 mm resolution, and frequently have contrast constraints as well - typically requiring T1 scans (e. g., MP-RAGE).

Image Registration Skull Stripping +1

Joint Frequency and Image Space Learning for MRI Reconstruction and Analysis

1 code implementation2 Jul 2020 Nalini M. Singh, Juan Eugenio Iglesias, Elfar Adalsteinsson, Adrian V. Dalca, Polina Golland

This is in contrast to most current deep learning approaches for image reconstruction that treat frequency and image space features separately and often operate exclusively in one of the two spaces.

Image Denoising MRI Reconstruction

An Auto-Encoder Strategy for Adaptive Image Segmentation

1 code implementation MIDL 2019 Evan M. Yu, Juan Eugenio Iglesias, Adrian V. Dalca, Mert R. Sabuncu

Thus there is a strong need for deep learning-based segmentation tools that do not require heavy supervision and can continuously adapt.

Image Segmentation Representation Learning +2

Partial Volume Segmentation of Brain MRI Scans of any Resolution and Contrast

2 code implementations21 Apr 2020 Benjamin Billot, Eleanor D. Robinson, Adrian V. Dalca, Juan Eugenio Iglesias

Partial voluming (PV) is arguably the last crucial unsolved problem in Bayesian segmentation of brain MRI with probabilistic atlases.

A Learning Strategy for Contrast-agnostic MRI Segmentation

3 code implementations MIDL 2019 Benjamin Billot, Douglas Greve, Koen van Leemput, Bruce Fischl, Juan Eugenio Iglesias, Adrian V. Dalca

These samples are produced using the generative model of the classical Bayesian segmentation framework, with randomly sampled parameters for appearance, deformation, noise, and bias field.

Brain Segmentation MRI segmentation +3

Unsupervised Deep Learning for Bayesian Brain MRI Segmentation

1 code implementation25 Apr 2019 Adrian V. Dalca, Evan Yu, Polina Golland, Bruce Fischl, Mert R. Sabuncu, Juan Eugenio Iglesias

To develop a deep learning-based segmentation model for a new image dataset (e. g., of different contrast), one usually needs to create a new labeled training dataset, which can be prohibitively expensive, or rely on suboptimal ad hoc adaptation or augmentation approaches.

Brain Image Segmentation Brain Segmentation +6

Large-scale mammography CAD with Deformable Conv-Nets

no code implementations19 Feb 2019 Stephen Morrell, Zbigniew Wojna, Can Son Khoo, Sebastien Ourselin, Juan Eugenio Iglesias

State-of-the-art deep learning methods for image processing are evolving into increasingly complex meta-architectures with a growing number of modules.

A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology

no code implementations22 Jun 2018 Juan Eugenio Iglesias, Ricardo Insausti, Garikoitz Lerma-Usabiaga, Martina Bocchetta, Koen van Leemput, Douglas N. Greve, Andre van der Kouwe, Bruce Fischl, Cesar Caballero-Gaudes, Pedro M Paz-Alonso

In this study, we present a probabilistic atlas of the thalamic nuclei built using ex vivo brain MRI scans and histological data, as well as the application of the atlas to in vivo MRI segmentation.

Bayesian Inference Hippocampus +2

Joint registration and synthesis using a probabilistic model for alignment of MRI and histological sections

no code implementations16 Jan 2018 Juan Eugenio Iglesias, Marc Modat, Loic Peter, Allison Stevens, Roberto Annunziata, Tom Vercauteren, Ed Lein, Bruce Fischl, Sebastien Ourselin

Here, we overcome this limitation with a probabilistic method that simultaneously solves for registration and synthesis directly on the target images, without any training data.

Bayesian Inference

Part-to-whole Registration of Histology and MRI using Shape Elements

no code implementations27 Aug 2017 Jonas Pichat, Juan Eugenio Iglesias, Sotiris Nousias, Tarek Yousry, Sebastien Ourselin, Marc Modat

We propose here a novel automatic approach to the joint problem of multimodal registration between histology and MRI, when only a fraction of tissue is available from histology.

Image Registration

Multi-Atlas Segmentation of Biomedical Images: A Survey

no code implementations10 Dec 2014 Juan Eugenio Iglesias, Mert Rory Sabuncu

Finally, our goal is to also present a perspective on the future of MAS, which, we believe, will be one of the dominant approaches in biomedical image segmentation.

Image Segmentation Segmentation +1

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