Monai: An open-source framework for deep learning in healthcare
Artificial Intelligence (AI) is having a tremendous impact across most areas of science.
Applications of AI in healthcare have the potential to improve our ability to detect, diagnose …
Applications of AI in healthcare have the potential to improve our ability to detect, diagnose …
Glioma survival analysis empowered with data engineering—a survey
Survival analysis is a critical task in glioma patient management due to the inter and intra
tumor heterogeneity. In clinical practice, clinicians estimate the survival with their …
tumor heterogeneity. In clinical practice, clinicians estimate the survival with their …
The ANTsX ecosystem for quantitative biological and medical imaging
Abstract The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of
multiple open-source software libraries which house top-performing algorithms used …
multiple open-source software libraries which house top-performing algorithms used …
GaNDLF: the generally nuanced deep learning framework for scalable end-to-end clinical workflows
Deep Learning (DL) has the potential to optimize machine learning in both the scientific and
clinical communities. However, greater expertise is required to develop DL algorithms, and …
clinical communities. However, greater expertise is required to develop DL algorithms, and …
[HTML][HTML] Residual Aligner-based Network (RAN): Motion-separable structure for coarse-to-fine discontinuous deformable registration
Deformable image registration, the estimation of the spatial transformation between different
images, is an important task in medical imaging. Deep learning techniques have been …
images, is an important task in medical imaging. Deep learning techniques have been …
[HTML][HTML] Prior knowledge based deep learning auto-segmentation in magnetic resonance imaging-guided radiotherapy of prostate cancer
Background and purpose Automation is desirable for organ segmentation in radiotherapy.
This study compared deep learning methods for auto-segmentation of organs-at-risk (OARs) …
This study compared deep learning methods for auto-segmentation of organs-at-risk (OARs) …
Meta-learning initializations for interactive medical image registration
We present a meta-learning framework for interactive medical image registration. Our
proposed framework comprises three components: a learning-based medical image …
proposed framework comprises three components: a learning-based medical image …
[HTML][HTML] Deep learning image registration for cardiac motion estimation in adult and fetal echocardiography via a focus on anatomic plausibility and texture quality of …
Temporal echocardiography image registration is important for cardiac motion estimation,
myocardial strain assessments, and stroke volume quantifications. Deep learning image …
myocardial strain assessments, and stroke volume quantifications. Deep learning image …
Regional deep atrophy: Using temporal information to automatically identify regions associated with Alzheimer's disease progression from longitudinal MRI
Longitudinal assessment of brain atrophy, particularly in the hippocampus, is a well-studied
biomarker for neurodegenerative diseases, such as Alzheimer's disease (AD). Estimating …
biomarker for neurodegenerative diseases, such as Alzheimer's disease (AD). Estimating …
Cross-Modality Image Registration Using a Training-Time Privileged Third Modality
In this work, we consider the task of pairwise cross-modality image registration, which may
benefit from exploiting additional images available only at training time from an additional …
benefit from exploiting additional images available only at training time from an additional …