Search Results for author: Andrew F. Laine

Found 15 papers, 3 papers with code

Robust Quantification of Percent Emphysema on CT via Domain Attention: the Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study

no code implementations28 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.

Computed Tomography (CT) Segmentation

TABSurfer: a Hybrid Deep Learning Architecture for Subcortical Segmentation

no code implementations13 Dec 2023 Aaron Cao, Vishwanatha M. Rao, Kejia Liu, Xinru Liu, Andrew F. Laine, Jia Guo

Subcortical segmentation remains challenging despite its important applications in quantitative structural analysis of brain MRI scans.


MAPSeg: Unified Unsupervised Domain Adaptation for Heterogeneous Medical Image Segmentation Based on 3D Masked Autoencoding and Pseudo-Labeling

1 code implementation16 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.

Domain Generalization Image Segmentation +5

Improving Across-Dataset Brain Tissue Segmentation Using Transformer

1 code implementation21 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.

Image Segmentation Medical Image Segmentation +2

Darwin's Neural Network: AI-based Strategies for Rapid and Scalable Cell and Coronavirus Screening

no code implementations22 Jul 2020 Sang Won Lee, Yueh-Ting Chiu, Philip Brudnicki, Audrey M. Bischoff, Angus Jelinek, Jenny Zijun Wang, Danielle R. Bogdanowicz, Andrew F. Laine, Jia Guo, Helen H. Lu

Recent advances in the interdisciplinary scientific field of machine perception, computer vision, and biomedical engineering underpin a collection of machine learning algorithms with a remarkable ability to decipher the contents of microscope and nanoscope images.

BIG-bench Machine Learning Instance Segmentation +1

Novel Subtypes of Pulmonary Emphysema Based on Spatially-Informed Lung Texture Learning

no code implementations9 Jul 2020 Jie Yang, Elsa D. Angelini, Pallavi P. Balte, Eric A. Hoffman, John H. M. Austin, Benjamin M. Smith, R. Graham Barr, Andrew F. Laine

Pulmonary emphysema overlaps considerably with chronic obstructive pulmonary disease (COPD), and is traditionally subcategorized into three subtypes previously identified on autopsy.

Computed Tomography (CT)

Segmentation with Residual Attention U-Net and an Edge-Enhancement Approach Preserves Cell Shape Features

1 code implementation15 Jan 2020 Nanyan Zhu, Chen Liu, Zakary S. Singer, Tal Danino, Andrew F. Laine, Jia Guo

The ability to extrapolate gene expression dynamics in living single cells requires robust cell segmentation, and one of the challenges is the amorphous or irregularly shaped cell boundaries.

Cell Segmentation Cell Tracking +2

Class-Aware Adversarial Lung Nodule Synthesis in CT Images

no code implementations28 Dec 2018 Jie Yang, Si-Qi Liu, Sasa Grbic, Arnaud Arindra Adiyoso Setio, Zhoubing Xu, Eli Gibson, Guillaume Chabin, Bogdan Georgescu, Andrew F. Laine, Dorin Comaniciu

Synthesizing the objects of interests, such as lung nodules, in medical images based on the distribution of annotated datasets can be helpful for improving the supervised learning tasks, especially when the datasets are limited by size and class balance.

Binary Classification General Classification

Discriminative analysis of the human cortex using spherical CNNs - a study on Alzheimer's disease diagnosis

no code implementations19 Dec 2018 Xinyang Feng, Jie Yang, Andrew F. Laine, Elsa D. Angelini

In neuroimaging studies, the human cortex is commonly modeled as a sphere to preserve the topological structure of the cortical surface.

General Classification

Discriminative Localization in CNNs for Weakly-Supervised Segmentation of Pulmonary Nodules

no code implementations4 Jul 2017 Xinyang Feng, Jie Yang, Andrew F. Laine, Elsa D. Angelini

Automated detection and segmentation of pulmonary nodules on lung computed tomography (CT) scans can facilitate early lung cancer diagnosis.

Computed Tomography (CT) General Classification +4

Explaining Radiological Emphysema Subtypes with Unsupervised Texture Prototypes: MESA COPD Study

no code implementations5 Dec 2016 Jie Yang, Elsa D. Angelini, Benjamin M. Smith, John H. M. Austin, Eric A. Hoffman, David A. Bluemke, R. Graham Barr, Andrew F. Laine

Pulmonary emphysema is traditionally subcategorized into three subtypes, which have distinct radiological appearances on computed tomography (CT) and can help with the diagnosis of chronic obstructive pulmonary disease (COPD).

Computed Tomography (CT)

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