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07/06/2023
To pretrain or not to pretrain? A case study of domain-specific pretraining for semantic segmentation in histopathology
Annotating medical imaging datasets is costly, so fine-tuning (or transf...
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07/06/2023
ADASSM: Adversarial Data Augmentation in Statistical Shape Models From Images
Statistical shape models (SSM) have been well-established as an excellen...
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05/23/2023
Point2SSM: Learning Morphological Variations of Anatomies from Point Cloud
We introduce Point2SSM, a novel unsupervised learning approach that can ...
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05/13/2023
Mesh2SSM: From Surface Meshes to Statistical Shape Models of Anatomy
Statistical shape modeling is the computational process of discovering s...
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05/09/2023
Fully Bayesian VIB-DeepSSM
Statistical shape modeling (SSM) enables population-based quantitative a...
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05/09/2023
Unsupervised Domain Adaptation for Semantic Segmentation via Feature-space Density Matching
Semantic segmentation is a critical step in automated image interpretati...
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05/09/2023
Can point cloud networks learn statistical shape models of anatomies?
Statistical Shape Modeling (SSM) is a valuable tool for investigating an...
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09/06/2022
Spatiotemporal Cardiac Statistical Shape Modeling: A Data-Driven Approach
Clinical investigations of anatomy's structural changes over time could ...
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09/06/2022
Statistical Shape Modeling of Biventricular Anatomy with Shared Boundaries
Statistical shape modeling (SSM) is a valuable and powerful tool to gene...
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05/25/2022
RENs: Relevance Encoding Networks
The manifold assumption for high-dimensional data assumes that the data ...
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05/13/2022
From Images to Probabilistic Anatomical Shapes: A Deep Variational Bottleneck Approach
Statistical shape modeling (SSM) directly from 3D medical images is an u...
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01/10/2022
Learning Population-level Shape Statistics and Anatomy Segmentation From Images: A Joint Deep Learning Model
Statistical shape modeling is an essential tool for the quantitative ana...
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11/13/2021
Leveraging Unsupervised Image Registration for Discovery of Landmark Shape Descriptor
In current biological and medical research, statistical shape modeling (...
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10/14/2021
DeepSSM: A Blueprint for Image-to-Shape Deep Learning Models
Statistical shape modeling (SSM) characterizes anatomical variations in ...
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10/28/2020
GENs: Generative Encoding Networks
Mapping data from and/or onto a known family of distributions has become...
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07/13/2020
Uncertain-DeepSSM: From Images to Probabilistic Shape Models
Statistical shape modeling (SSM) has recently taken advantage of advance...
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11/24/2019
dpVAEs: Fixing Sample Generation for Regularized VAEs
Unsupervised representation learning via generative modeling is a staple...
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06/28/2019
SetGANs: Enforcing Distributional Accuracy in Generative Adversarial Networks
This paper addresses the ability of generative adversarial networks (GAN...
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06/13/2019
CoopSubNet: Cooperating Subnetwork for Data-Driven Regularization of Deep Networks under Limited Training Budgets
Deep networks are an integral part of the current machine learning parad...
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03/06/2019
Mixture Modeling of Global Shape Priors and Autoencoding Local Intensity Priors for Left Atrium Segmentation
Difficult image segmentation problems, for instance left atrium MRI, can...
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10/03/2018
On the Evaluation and Validation of Off-the-shelf Statistical Shape Modeling Tools: A Clinical Application
Statistical shape modeling (SSM) has proven useful in many areas of biol...
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09/30/2018
