Imageflownet: Forecasting multiscale image-level trajectories of disease progression with irregularly-sampled longitudinal medical images
Advances in medical imaging technologies have enabled the collection of longitudinal
images, which involve repeated scanning of the same patients over time, to monitor disease …
images, which involve repeated scanning of the same patients over time, to monitor disease …
A Brief Overview of Optimization-Based Algorithms for MRI Reconstruction Using Deep Learning
W Bian - arXiv preprint arXiv:2406.02626, 2024 - arxiv.org
Magnetic resonance imaging (MRI) is renowned for its exceptional soft tissue contrast and
high spatial resolution, making it a pivotal tool in medical imaging. The integration of deep …
high spatial resolution, making it a pivotal tool in medical imaging. The integration of deep …
Provably convergent learned inexact descent algorithm for low-dose ct reconstruction
Abstract We propose an Efficient Inexact Learned Descent-type Algorithm (ELDA) for a class
of nonconvex and nonsmooth variational models, where the regularization consists of a …
of nonconvex and nonsmooth variational models, where the regularization consists of a …
Fusing Multiple Information Sources for Predictive Cardiac Modeling
Z Feng - 2024 - cdr.lib.unc.edu
Echocardiography is typically the first-line imaging study for most cardiac diagnoses due to
its versatility and cost-effectiveness. There is considerable interest in predictive machine …
its versatility and cost-effectiveness. There is considerable interest in predictive machine …
CitationMap: A Python Tool to Identify and Visualize Your Google Scholar Citations Around the World
C Liu - Authorea Preprints, 2024 - advance.sagepub.com
CitationMap: A Python Tool to Identify and Visualize Your Google Scholar Citations Around
the World Page 1 P osted on 7 Aug 2024 — CC-BY-NC-SA 4 — h ttps://doi.org/10.36227/techrx …
the World Page 1 P osted on 7 Aug 2024 — CC-BY-NC-SA 4 — h ttps://doi.org/10.36227/techrx …
Exploring Hybrid CNN-Transformer for Schizophrenia Classification using Structural MRI
Schizophrenia diagnosis is clinically difficult due to the lack of biomarkers associated with
the disease. While machine learning algorithms and convolutional neural networks (CNNs) …
the disease. While machine learning algorithms and convolutional neural networks (CNNs) …