Obstetrics & Gynecology

Pregnancy

Latest AI and machine learning research in pregnancy for healthcare professionals.

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Pyramid Self-contrastive Learning Framework for Test-time Ultrasound Image Denoising

The inherent electronic and speckle noise complicates clinical interpretation of ultrasound images. ...

Detection of Hepatocellular Carcinoma from B-Mode and Contrast-Enhanced Ultrasound Using a Dual-Path Convolutional Network

Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide,...

Optimizing Screening for Intrauterine Fetal Growth Restriction in Low-Resource Settings Using 2D Ultrasound: A Deep Learning Approach

Severe fetal growth restriction (sFGR) affects 5 to 10% of pregnancies worldwide and is a major cont...

Echo-α: Large Agentic Multimodal Reasoning Model for Ultrasound Interpretation

Ultrasound interpretation requires both precise lesion localization and holistic clinical reasoning,...

SAMe: A Semantic Anatomy Mapping Engine for Robotic Ultrasound

Robotic ultrasound has advanced local image-driven control, contact regulation, and view optimizatio...

Multivariate Gaussian NeRF for Wide Field-of-View Ultrasound Reconstruction

Wide Field-of-View (WFoV) reconstruction enhances 3D ultrasound imaging by providing valuable anatom...

A machine learning approach to infer DNase1L3 activity from plasma cell-free DNA fragmentomics

DNase1L3 is an endonuclease that fragments DNA during apoptosis and digests DNA from microparticles ...

Focus on What Matters: Two-Stage ROI-Aware Refinement for Anatomy-Preserving Fetal Ultrasound Reconstruction

Measurement-critical ultrasound tasks often depend on a small anatomical region, making global recon...

Attention-ResUNet for Automated Fetal Head Segmentation

Automated fetal head segmentation in ultrasound images is critical for accurate biometric measuremen...

PolarMAE: Efficient Fetal Ultrasound Pre-training via Semantic Screening and Polar-Guided Masking

Intelligent fetal ultrasound (US) interpretation is crucial for prenatal diagnosis, but high annotat...

PBE-UNet: A light weight Progressive Boundary-Enhanced U-Net with Scale-Aware Aggregation for Ultrasound Image Segmentation

Accurate lesion segmentation in ultrasound images is essential for preventive screening and clinical...

ReXSonoVQA: A Video QA Benchmark for Procedure-Centric Ultrasound Understanding

Ultrasound acquisition requires skilled probe manipulation and real-time adjustments. Vision-languag...

A Workflow to Efficiently Generate Dense Tissue Ground Truth Masks for Digital Breast Tomosynthesis

Digital breast tomosynthesis (DBT) is now the standard of care for breast cancer screening in the US...

ReXSonoVQA: A Video QA Benchmark for Procedure-Centric Ultrasound Understanding

Ultrasound acquisition requires skilled probe manipulation and real-time adjustments. Vision-languag...

MonoUNet: A Robust Tiny Neural Network for Automated Knee Cartilage Segmentation on Point-of-Care Ultrasound Devices

Objective: To develop a robust and compact deep learning model for automated knee cartilage segmenta...

Validated Synthetic Patient Generation for Small Longitudinal Cohorts: Coagulation Dynamics Across Pregnancy

Small longitudinal clinical cohorts, common in maternal health, rare diseases, and early-phase trial...

Data-efficient Self-Supervised Diffusion Learning for Detecting Myofascial Pain in Upper Trapezius Muscle with B-mode Ultrasound Videos

Deep learning has transformed medical image and video analysis, but it usually requires large, well ...

Ultrasound-CLIP: Semantic-Aware Contrastive Pre-training for Ultrasound Image-Text Understanding

Ultrasound imaging is widely used in clinical diagnostics due to its real-time capability and radiat...

Developmental brain age gap in prematurity and postnatally emerging delay in congenital heart disease

Brain development follows a precisely regulated biological timetable, with defined periods of vulner...

Measuring the Unmeasurable: A Diagnostic Sensor for AI Reasoning Pathology in Sequential Clinical Decision-Making

Large Language Models achieve impressive accuracy on medical benchmarks that present clinical inform...

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