no code implementations • 28 Feb 2024 • Xuzhe Zhang, Elsa D. Angelini, Eric A. Hoffman, Karol E. Watson, Benjamin M. Smith, R. Graham Barr, Andrew F. Laine
Robust quantification of pulmonary emphysema on computed tomography (CT) remains challenging for large-scale research studies that involve scans from different scanner types and for translation to clinical scans.
1 code implementation • 16 Mar 2023 • Xuzhe Zhang, Yuhao Wu, Elsa Angelini, Ang Li, Jia Guo, Jerod M. Rasmussen, Thomas G. O'Connor, Pathik D. Wadhwa, Andrea Parolin Jackowski, Hai Li, Jonathan Posner, Andrew F. Laine, Yun Wang
In this study, we introduce Masked Autoencoding and Pseudo-Labeling Segmentation (MAPSeg), a $\textbf{unified}$ UDA framework with great versatility and superior performance for heterogeneous and volumetric medical image segmentation.
1 code implementation • 21 Jan 2022 • Vishwanatha M. Rao, Zihan Wan, Soroush Arabshahi, David J. Ma, Pin-Yu Lee, Ye Tian, Xuzhe Zhang, Andrew F. Laine, Jia Guo
Transformers have demonstrated success in natural image segmentation and have recently been applied to 3D medical image segmentation tasks due to their ability to capture long-distance relationships in the input where the local receptive fields of CNNs struggle.
1 code implementation • 14 Jun 2021 • Xinzi He, Jia Guo, Xuzhe Zhang, Hanwen Bi, Sarah Gerard, David Kaczka, Amin Motahari, Eric Hoffman, Joseph Reinhardt, R. Graham Barr, Elsa Angelini, Andrew Laine
We introduce a recursive refinement network (RRN) for unsupervised medical image registration, to extract multi-scale features, construct normalized local cost correlation volume and recursively refine volumetric deformation vector fields.
Ranked #1 on Image Registration on DIR-LAB COPDgene
1 code implementation • 28 May 2021 • Xuzhe Zhang, Xinzi He, Jia Guo, Nabil Ettehadi, Natalie Aw, David Semanek, Jonathan Posner, Andrew Laine, Yun Wang
Magnetic resonance imaging (MRI) noninvasively provides critical information about how human brain structures develop across stages of life.
Generative Adversarial Network Vocal Bursts Intensity Prediction