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Segment anything model for medical images?
Abstract The Segment Anything Model (SAM) is the first foundation model for general image
segmentation. It has achieved impressive results on various natural image segmentation …
segmentation. It has achieved impressive results on various natural image segmentation …
Application and prospects of AI-based radiomics in ultrasound diagnosis
Artificial intelligence (AI)-based radiomics has attracted considerable research attention in
the field of medical imaging, including ultrasound diagnosis. Ultrasound imaging has unique …
the field of medical imaging, including ultrasound diagnosis. Ultrasound imaging has unique …
Deep learning for the harmonization of structural MRI scans: a survey
Medical imaging datasets for research are frequently collected from multiple imaging centers
using different scanners, protocols, and settings. These variations affect data consistency …
using different scanners, protocols, and settings. These variations affect data consistency …
Synthetic optical coherence tomography angiographs for detailed retinal vessel segmentation without human annotations
Optical coherence tomography angiography (OCTA) is a non-invasive imaging modality that
can acquire high-resolution volumes of the retinal vasculature and aid the diagnosis of …
can acquire high-resolution volumes of the retinal vasculature and aid the diagnosis of …
Feature-conditioned cascaded video diffusion models for precise echocardiogram synthesis
Image synthesis is expected to provide value for the translation of machine learning
methods into clinical practice. Fundamental problems like model robustness, domain …
methods into clinical practice. Fundamental problems like model robustness, domain …
FetalBrainAwareNet: bridging GANs with anatomical insight for fetal ultrasound brain plane synthesis
Over the past decade, deep-learning (DL) algorithms have become a promising tool to aid
clinicians in identifying fetal head standard planes (FHSPs) during ultrasound (US) …
clinicians in identifying fetal head standard planes (FHSPs) during ultrasound (US) …
Semi-supervised standard-dose PET image generation via region-adaptive normalization and structural consistency constraint
Positron Emission Tomography (PET) is an important nuclear medical imaging technique,
and has been widely used in clinical applications, eg, tumor detection and brain disease …
and has been widely used in clinical applications, eg, tumor detection and brain disease …
US2Mask: Image-to-mask generation learning via a conditional GAN for cardiac ultrasound image segmentation
Cardiac ultrasound (US) image segmentation is vital for evaluating clinical indices, but it
often demands a large dataset and expert annotations, resulting in high costs for deep …
often demands a large dataset and expert annotations, resulting in high costs for deep …
Echonet-synthetic: Privacy-preserving video generation for safe medical data sharing
To make medical datasets accessible without sharing sensitive patient information, we
introduce a novel end-to-end approach for generative de-identification of dynamic medical …
introduce a novel end-to-end approach for generative de-identification of dynamic medical …
FetusMapV2: Enhanced fetal pose estimation in 3D ultrasound
Fetal pose estimation in 3D ultrasound (US) involves identifying a set of associated fetal
anatomical landmarks. Its primary objective is to provide comprehensive information about …
anatomical landmarks. Its primary objective is to provide comprehensive information about …