ahajournals.org

Synthetic Contrast-Free LGE via Diffusion-Based Framework in Acute MI for Image Quality and Quantitative Scar Analysis

This study aims to develop a diffusion model-based framework for generating late gadolinium enhancement (LGE)-like images without contrast. The resulting synthetic images are then comprehensively ...
The Lancet

End-to-end deep learning model for the diagnosis and segmentation of primary retroperitoneal neoplasm: a multicenter cohort study

aDepartment of Urology, Shanghai Changhai Hospital, Naval Medical University, Shanghai, China bDepartment of Radiology, Shanghai Changhai Hospital, Naval Medical University, Shanghai, China ...
PNAS

PyReconstruct: A fully open-source, collaborative successor to Reconstruct

In neuroscience, the emerging field of connectomics has produced annotation tools for reconstruction that prioritize circuit connectivity across microns to centimeters and farther. Determining the ...
GitHub

SLOctolyzer: Analysis toolkit for automatic segmentation and measurement of retinal vessels on SLO images

Analysis toolkit for automatic segmentation and measurement of retinal vessels for confocal, near infra-red scanning laser ophthalmoscopy (SLO) images. SLOctolyzer is a fully automatic pipeline which ...
Frontiers

suMRak: a multi-tool solution for preclinical brain MRI data analysis

Magnetic resonance imaging (MRI) is invaluable for understanding brain disorders, but data complexity poses a challenge in experimental research. In this study, we introduce suMRak, a MATLAB ...
Cancer Research

Deep Learning–Based 3D Single-Cell Imaging Analysis Pipeline Enables Quantification of Cell–Cell Interaction Dynamics in the Tumor Microenvironment

1Center for Quantitative Systems Biology, Department of Physics, Hong Kong Baptist University, Hong Kong SAR, P.R. China. Search for other works by this author on: 1Center for Quantitative Systems ...
Frontiers

Deep learning for the rapid automatic segmentation of forearm muscle boundaries from ultrasound datasets

Ultrasound (US) is widely used in the clinical diagnosis and treatment of musculoskeletal diseases. However, the low efficiency and non-uniformity of artificial recognition hinder the application and ...