no code implementations • 4 Mar 2024 • Camilo Calixto, Camilo Jaimes, Matheus D. Soldatelli, Simon K. Warfield, Ali Gholipour, Davood Karimi
Diffusion-weighted Magnetic Resonance Imaging (dMRI) is increasingly used to study the fetal brain in utero.
no code implementations • 22 Dec 2023 • Rizhong Lin, Ali Gholipour, Jean-Philippe Thiran, Davood Karimi, Hamza Kebiri, Meritxell Bach Cuadra
However, these models face domain shift challenges when test and train data are from different scanners and protocols, or when the models are applied to data with inherent variations such as the developing brains of infants and children scanned at various ages.
1 code implementation • 2 Oct 2023 • Razieh Faghihpirayesh, Davood Karimi, Deniz Erdoğmuş, Ali Gholipour
Evaluations on independent test data show that our method achieves accurate brain extraction on heterogeneous test data acquired with different scanners, on pathological brains, and at various gestational stages.
no code implementations • 22 Aug 2023 • Yihan Wu, Lana Vasung, Camilo Calixto, Ali Gholipour, Davood Karimi
The new computational method and results are useful for assessing normal and abnormal development of the structural connectome early in life.
no code implementations • 7 Jul 2023 • Davood Karimi, Hamza Kebiri, Ali Gholipour
Our method promises a drastic improvement in accuracy and reproducibility of cross-subject dMRI studies that are routinely used in neuroscience and medical research.
no code implementations • 5 Jul 2023 • Hamza Kebiri, Ali Gholipour, Meritxell Bach Cuadra, Davood Karimi
The new methods can serve many critically important clinical and scientific applications that require accurate and reliable non-invasive segmentation of white matter tracts.
no code implementations • 28 Apr 2023 • Rui Nian, Guoyao Zhang, Yao Sui, Yuqi Qian, Qiuying Li, Mingzhang Zhao, Jianhui Li, Ali Gholipour, Simon K. Warfield
By the nature of limited receptive fields, however, those architectures are subject to representing long-range spatial dependencies of the voxel intensities in MRI images.
no code implementations • 10 Oct 2022 • Arvind Balachandrasekaran, Davood Karimi, Camilo Jaimes, Ali Gholipour
This problem of estimating the susceptibility map is ill posed.
no code implementations • 5 May 2022 • Davood Karimi, Ali Gholipour
We use the biomarker atlas, atlas reliability map, and alignment error map, in addition to the dMRI signal, as inputs to a deep learning model for biomarker estimation.
1 code implementation • 2 May 2022 • Razieh Faghihpirayesh, Davood Karimi, Deniz Erdogmus, Ali Gholipour
Fast and accurate segmentation of the fetal brain on fetal MRI is required to achieve real-time fetal head pose estimation and motion tracking for slice re-acquisition and steering.
no code implementations • 20 Apr 2022 • Kelly Payette, Hongwei Li, Priscille de Dumast, Roxane Licandro, Hui Ji, Md Mahfuzur Rahman Siddiquee, Daguang Xu, Andriy Myronenko, Hao liu, Yuchen Pei, Lisheng Wang, Ying Peng, Juanying Xie, Huiquan Zhang, Guiming Dong, Hao Fu, Guotai Wang, ZunHyan Rieu, Donghyeon Kim, Hyun Gi Kim, Davood Karimi, Ali Gholipour, Helena R. Torres, Bruno Oliveira, João L. Vilaça, Yang Lin, Netanell Avisdris, Ori Ben-Zvi, Dafna Ben Bashat, Lucas Fidon, Michael Aertsen, Tom Vercauteren, Daniel Sobotka, Georg Langs, Mireia Alenyà, Maria Inmaculada Villanueva, Oscar Camara, Bella Specktor Fadida, Leo Joskowicz, Liao Weibin, Lv Yi, Li Xuesong, Moona Mazher, Abdul Qayyum, Domenec Puig, Hamza Kebiri, Zelin Zhang, Xinyi Xu, Dan Wu, Kuanlun Liao, Yixuan Wu, Jintai Chen, Yunzhi Xu, Li Zhao, Lana Vasung, Bjoern Menze, Meritxell Bach Cuadra, Andras Jakab
Automatic segmentation of the developing fetal brain is a vital step in the quantitative analysis of prenatal neurodevelopment both in the research and clinical context.
no code implementations • 25 Mar 2022 • Davood Karimi, Caitlin K. Rollins, Clemente Velasco-Annis, Abdelhakim Ouaalam, Ali Gholipour
However, effective training of a deep learning model to perform this task requires a large number of training images to represent the rapid development of the transient fetal brain structures.
no code implementations • 14 Jan 2022 • Davood Karimi, Ali Gholipour
Estimations produced by our method with six diffusion-weighted measurements are comparable with those of standard estimation methods with 30-88 diffusion-weighted measurements.
no code implementations • 21 Nov 2021 • Davood Karimi, Simon K. Warfield, Ali Gholipour
Here, we propose a deep learning method to estimate the diffusion tensor and compute the estimation uncertainty.
no code implementations • NeuroImage 2021 • Davood Karimi, Lana Vasung, Camilo Jaimes, Fedel Machado-Rivas, Simon K. Warfield, Ali Gholipour
Our study demonstrates the potential of data-driven methods for improving the accuracy and robustness of fODF estimation.
1 code implementation • 26 Feb 2021 • Davood Karimi, Serge Vasylechko, Ali Gholipour
We show that the proposed model can achieve segmentation accuracies that are better than the state of the art CNNs on three datasets.
1 code implementation • 19 Jun 2020 • Davood Karimi, Lana Vasung, Camilo Jaimes, Fedel Machado-Rivas, Shadab Khan, Simon K. Warfield, Ali Gholipour
Existing methods for estimating the number and orientations of fascicles in an imaging voxel either depend on non-convex optimization techniques that are sensitive to initialization and measurement noise, or are prone to predicting spurious fascicles.
no code implementations • 30 May 2020 • Davood Karimi, Simon K. Warfield, Ali Gholipour
Here, we study the role of transfer learning for training fully convolutional networks (FCNs) for medical image segmentation.
2 code implementations • 27 Apr 2020 • Haoran Dou, Davood Karimi, Caitlin K. Rollins, Cynthia M. Ortinau, Lana Vasung, Clemente Velasco-Annis, Abdelhakim Ouaalam, Xin Yang, Dong Ni, Ali Gholipour
Automatic segmentation of the cortical plate, on the other hand, is challenged by the relatively low resolution of the reconstructed fetal brain MRI scans compared to the thin structure of the cortical plate, partial voluming, and the wide range of variations in the morphology of the cortical plate as the brain matures during gestation.
1 code implementation • 12 Apr 2020 • Davood Karimi, Ali Gholipour
We show that different datasets, representing different imaging modalities and/or different organs of interest, have distinct spectral signatures, which can be used to identify whether or not a test image is similar to the images used to train a model.
no code implementations • 5 Dec 2019 • Davood Karimi, Haoran Dou, Simon K. Warfield, Ali Gholipour
Then, we review studies that have dealt with label noise in deep learning for medical image analysis.
2 code implementations • 25 Sep 2019 • Ayush Singh, Seyed Sadegh Mohseni Salehi, Ali Gholipour
Nevertheless, visual monitoring of fetal motion based on displayed slices, and navigation at the level of stacks-of-slices is inefficient.
no code implementations • 21 Sep 2018 • Seyed Raein Hashemi, Sanjay P. Prabhu, Simon K. Warfield, Ali Gholipour
Using our proposed training strategy based on similarity loss functions and patch prediction fusion we decrease the number of parameters in the network, reduce the complexity of the training process focusing the attention on less number of tasks, while mitigating the effects of data imbalance between labels and inaccuracies near patch borders.
no code implementations • 28 Mar 2018 • Seyed Raein Hashemi, Seyed Sadegh Mohseni Salehi, Deniz Erdogmus, Sanjay P. Prabhu, Simon K. Warfield, Ali Gholipour
One of the major challenges in training such networks raises when data is unbalanced, which is common in many medical imaging applications such as lesion segmentation where lesion class voxels are often much lower in numbers than non-lesion voxels.
no code implementations • 15 Mar 2018 • Seyed Sadegh Mohseni Salehi, Shadab Khan, Deniz Erdogmus, Ali Gholipour
Our results show that in such registration applications that are amendable to learning, the proposed deep learning methods with geodesic loss minimization can achieve accurate results with a wide capture range in real-time (<100ms).
1 code implementation • 25 Oct 2017 • Seyed Sadegh Mohseni Salehi, Seyed Raein Hashemi, Clemente Velasco-Annis, Abdelhakim Ouaalam, Judy A. Estroff, Deniz Erdogmus, Simon K. Warfield, Ali Gholipour
We aimed to develop a fully automatic segmentation method that independently segments sections of the fetal brain in 2D fetal MRI slices in real-time.
2 code implementations • 18 Jun 2017 • Seyed Sadegh Mohseni Salehi, Deniz Erdogmus, Ali Gholipour
One of the main challenges in training these networks is data imbalance, which is particularly problematic in medical imaging applications such as lesion segmentation where the number of lesion voxels is often much lower than the number of non-lesion voxels.
no code implementations • 6 Mar 2017 • Seyed Sadegh Mohseni Salehi, Deniz Erdogmus, Ali Gholipour
Brain extraction or whole brain segmentation is an important first step in many of the neuroimage analysis pipelines.