no code implementations • 3 Mar 2023 • Yuli Wang, Anqi Feng, Yuan Xue, Lianrui Zuo, Yihao Liu, Ari M. Blitz, Mark G. Luciano, Aaron Carass, Jerry L. Prince
Normal pressure hydrocephalus~(NPH) is a brain disorder associated with enlarged ventricles and multiple cognitive and motor symptoms.
no code implementations • 18 Feb 2023 • Zhangxing Bian, Muhan Shao, Jiachen Zhuo, Rao P. Gullapalli, Aaron Carass, Jerry L. Prince
Connectivity information derived from diffusion-weighted magnetic resonance images~(DW-MRIs) plays an important role in studying human subcortical gray matter structures.
no code implementations • 1 Feb 2023 • Lianrui Zuo, Yuan Xue, Blake E. Dewey, Yihao Liu, Jerry L. Prince, Aaron Carass
Image quality control (IQC) can be used in automated magnetic resonance (MR) image analysis to exclude erroneous results caused by poorly acquired or artifact-laden images.
no code implementations • 18 Jan 2023 • Zhangxing Bian, Fangxu Xing, Jinglun Yu, Muhan Shao, Yihao Liu, Aaron Carass, Jiachen Zhuo, Jonghye Woo, Jerry L. Prince
However, this technique faces several challenges such as tag fading, large motion, long computation times, and difficulties in obtaining diffeomorphic incompressible flow fields.
no code implementations • 15 Jan 2023 • Chang Yan, Muhan Shao, Zhangxing Bian, Anqi Feng, Yuan Xue, Jiachen Zhuo, Rao P. Gullapalli, Aaron Carass, Jerry L. Prince
After registration of these contrasts and isolation of the thalamus, we use the uniform manifold approximation and projection (UMAP) method for dimensionality reduction to produce a low-dimensional representation of the data within the thalamus.
1 code implementation • 12 Dec 2022 • Yihao Liu, Junyu Chen, Shuwen Wei, Aaron Carass, Jerry Prince
We show that for a 2D transformation, four unique finite difference approximations of $|J|$'s must be positive to ensure the entire domain is invertible and free of folding at the pixel level.
no code implementations • 12 Dec 2022 • Lianrui Zuo, Yihao Liu, Yuan Xue, Blake E. Dewey, Murat Bilgel, Ellen M. Mowry, Scott D. Newsome, Peter A. Calabresi, Susan M. Resnick, Jerry L. Prince, Aaron Carass
HACA3 is also robust to imaging artifacts and can be trained and applied to any set of MR contrasts.
no code implementations • 6 Sep 2022 • Samuel W. Remedios, Shuo Han, Yuan Xue, Aaron Carass, Trac D. Tran, Dzung L. Pham, Jerry L. Prince
In 2D multi-slice magnetic resonance (MR) acquisition, the through-plane signals are typically of lower resolution than the in-plane signals.
no code implementations • 5 Aug 2022 • Germain Morilhat, Naomi Kifle, Sandra FinesilverSmith, Bram Ruijsink, Vittoria Vergani, Habtamu Tegegne Desita, Zerubabel Tegegne Desita, Esther Puyol-Anton, Aaron Carass, Andrew P. King
This work showcases, for the first time, the potential of DL in automating the process of effusion assessment from ultrasound in LMIC settings where there is often a lack of experienced radiologists to perform such tasks.
no code implementations • 10 May 2022 • Lianrui Zuo, Yihao Liu, Yuan Xue, Shuo Han, Murat Bilgel, Susan M. Resnick, Jerry L. Prince, Aaron Carass
Disentangling anatomical and contrast information from medical images has gained attention recently, demonstrating benefits for various image analysis tasks.
1 code implementation • 5 Mar 2022 • Yihao Liu, Lianrui Zuo, Shuo Han, Yuan Xue, Jerry L. Prince, Aaron Carass
The majority of deep learning (DL) based deformable image registration methods use convolutional neural networks (CNNs) to estimate displacement fields from pairs of moving and fixed images.
no code implementations • 29 Oct 2021 • Kshitiz Upadhyay, Dimitris G. Giovanis, Ahmed Alshareef, Andrew K. Knutsen, Curtis L. Johnson, Aaron Carass, Philip V. Bayly, Michael D. Shields, K. T. Ramesh
This framework is demonstrated on a 2D subject-specific head model, where the goal is to quantify uncertainty in the simulated strain fields (i. e., output), given variability in the material properties of different brain substructures (i. e., input).
1 code implementation • 31 Mar 2021 • Shuo Han, Samuel Remedios, Aaron Carass, Michael Schär, Jerry L. Prince
To super-resolve the through-plane direction of a multi-slice 2D magnetic resonance (MR) image, its slice selection profile can be used as the degeneration model from high resolution (HR) to low resolution (LR) to create paired data when training a supervised algorithm.
no code implementations • 24 Mar 2021 • Lianrui Zuo, Blake E. Dewey, Aaron Carass, Yihao Liu, Yufan He, Peter A. Calabresi, Jerry L. Prince
Accuracy and consistency are two key factors in computer-assisted magnetic resonance (MR) image analysis.
1 code implementation • 4 Mar 2021 • Jacob C. Reinhold, Aaron Carass, Jerry L. Prince
Precision medicine involves answering counterfactual questions such as "Would this patient respond better to treatment A or treatment B?"
no code implementations • 14 Jan 2021 • Xiaofeng Liu, Fangxu Xing, Jerry L. Prince, Aaron Carass, Maureen Stone, Georges El Fakhri, Jonghye Woo
Tagged magnetic resonance imaging (MRI) is a widely used imaging technique for measuring tissue deformation in moving organs.
1 code implementation • 7 Jul 2020 • Yufan He, Aaron Carass, Lianrui Zuo, Blake E. Dewey, Jerry L. Prince
However, training a model for each target domain is time consuming and computationally expensive, even infeasible when target domain data are scarce or source data are unavailable due to data privacy.
1 code implementation • 11 Feb 2020 • Jacob C. Reinhold, Yufan He, Shizhong Han, Yunqiang Chen, Dashan Gao, Junghoon Lee, Jerry L. Prince, Aaron Carass
Medical images are increasingly used as input to deep neural networks to produce quantitative values that aid researchers and clinicians.
2 code implementations • 11 Feb 2020 • Jacob C. Reinhold, Yufan He, Shizhong Han, Yunqiang Chen, Dashan Gao, Junghoon Lee, Jerry L. Prince, Aaron Carass
Medical images are often used to detect and characterize pathology and disease; however, automatically identifying and segmenting pathology in medical images is challenging because the appearance of pathology across diseases varies widely.
1 code implementation • 11 Dec 2018 • Jacob C. Reinhold, Blake E. Dewey, Aaron Carass, Jerry L. Prince
Image synthesis learns a transformation from the intensity features of an input image to yield a different tissue contrast of the output image.
no code implementations • 12 Sep 2018 • Heran Yang, Jian Sun, Aaron Carass, Can Zhao, Junghoon Lee, Zongben Xu, Jerry Prince
The cycleGAN is becoming an influential method in medical image synthesis.
no code implementations • 6 Jun 2018 • Lena Maier-Hein, Matthias Eisenmann, Annika Reinke, Sinan Onogur, Marko Stankovic, Patrick Scholz, Tal Arbel, Hrvoje Bogunovic, Andrew P. Bradley, Aaron Carass, Carolin Feldmann, Alejandro F. Frangi, Peter M. Full, Bram van Ginneken, Allan Hanbury, Katrin Honauer, Michal Kozubek, Bennett A. Landman, Keno März, Oskar Maier, Klaus Maier-Hein, Bjoern H. Menze, Henning Müller, Peter F. Neher, Wiro Niessen, Nasir Rajpoot, Gregory C. Sharp, Korsuk Sirinukunwattana, Stefanie Speidel, Christian Stock, Danail Stoyanov, Abdel Aziz Taha, Fons van der Sommen, Ching-Wei Wang, Marc-André Weber, Guoyan Zheng, Pierre Jannin, Annette Kopp-Schneider
International challenges have become the standard for validation of biomedical image analysis methods.
no code implementations • 14 Mar 2018 • Yufan He, Aaron Carass, Bruno M. Jedynak, Sharon D. Solomon, Shiv Saidha, Peter A. Calabresi, Jerry L. Prince
Optical coherence tomography (OCT) is a noninvasive imaging modality which can be used to obtain depth images of the retina.
no code implementations • 26 Feb 2018 • Can Zhao, Aaron Carass, Blake E. Dewey, Jerry L. Prince
This paper presents a self super-resolution~(SSR) algorithm, which does not use any external atlas images, yet can still resolve HR images only reliant on the acquired LR image.