Pregnancy

Speckle2Self: Self-Supervised Ultrasound Speckle Reduction Without Clean Data

Image denoising is a fundamental task in computer vision, particularly in medical ultrasound (US) imaging, where speckle noise significantly degrades image quality. Although recent advancements in deep neural networks have led to substantial improvements in denoising for natural images, these methods cannot be directly applied to US speckle noise, as it is not purely random. Instead, US speckle ...

Magneto-radiative modelling and artificial neural network optimization of biofluid flow in a stenosed arterial domain

The increasing complexity of cardiovascular diseases and limitations in traditional healing methods mandate the invention of new drug delivery systems that assure targeted, effective, and regulated treatments, contributing directly to UN SDGs 3 and 9, thereby encouraging the utilization of sustainable medical technologies in healthcare. This study investigates the flow of a Casson-Maxwell nanofl...

Miniaturized optically-generated Bessel beam ultrasound for volumetric transcranial brain stimulation

Non-invasive stimulation of small, variably shaped brain sub-regions is crucial for advancing our understanding of brain functions. Current ultrasou...

AURA-CVC: Autonomous Ultrasound-guided Robotic Assistance for Central Venous Catheterization

Purpose: Central venous catheterization (CVC) is a critical medical procedure for vascular access, hemodynamic monitoring, and life-saving intervent...

A novel framework for fully-automated co-registration of intravascular ultrasound and optical coherence tomography imaging data

Aims: To develop a deep-learning (DL) framework that will allow fully automated longitudinal and circumferential co-registration of intravascular ul...

Vers un cadre ontologique pour la gestion des comp{é}tences : {à} des fins de formation, de recrutement, de m{é}tier, ou de recherches associ{é}es

The rapid transformation of the labor market, driven by technological advancements and the digital economy, requires continuous competence developme...

Self-supervised Deep Learning for Denoising in Ultrasound Microvascular Imaging

Ultrasound microvascular imaging (UMI) is often hindered by low signal-to-noise ratio (SNR), especially in contrast-free or deep tissue scenarios, w...

Latent Motion Profiling for Annotation-free Cardiac Phase Detection in Adult and Fetal Echocardiography Videos

The identification of cardiac phase is an essential step for analysis and diagnosis of cardiac function. Automatic methods, especially data-driven m...

ViTaL: A Multimodality Dataset and Benchmark for Multi-pathological Ovarian Tumor Recognition

Ovarian tumor, as a common gynecological disease, can rapidly deteriorate into serious health crises when undetected early, thus posing significant ...

EdgeSRIE: A hybrid deep learning framework for real-time speckle reduction and image enhancement on portable ultrasound systems

Speckle patterns in ultrasound images often obscure anatomical details, leading to diagnostic uncertainty. Recently, various deep learning (DL)-base...

Hybrid-View Attention Network for Clinically Significant Prostate Cancer Classification in Transrectal Ultrasound

Prostate cancer (PCa) is a leading cause of cancer-related mortality in men, and accurate identification of clinically significant PCa (csPCa) is cr...

UltraDfeGAN: Detail-Enhancing Generative Adversarial Networks for High-Fidelity Functional Ultrasound Synthesis

Functional ultrasound (fUS) is a neuroimaging technique known for its high spatiotemporal resolution, enabling non-invasive observation of brain act...

LANTERN: A Machine Learning Framework for Lipid Nanoparticle Transfection Efficiency Prediction

The discovery of new ionizable lipids for efficient lipid nanoparticle (LNP)-mediated RNA delivery remains a critical bottleneck for RNA-based thera...

3D Heart Reconstruction from Sparse Pose-agnostic 2D Echocardiographic Slices

Echocardiography (echo) plays an indispensable role in the clinical practice of heart diseases. However, ultrasound imaging typically provides only ...

PAL: Designing Conversational Agents as Scalable, Cooperative Patient Simulators for Palliative-Care Training

Effective communication in serious illness and palliative care is essential but often under-taught due to limited access to training resources like ...

Medical-Knowledge Driven Multiple Instance Learning for Classifying Severe Abdominal Anomalies on Prenatal Ultrasound

Fetal abdominal malformations are serious congenital anomalies that require accurate diagnosis to guide pregnancy management and reduce mortality. A...

SonoGym: High Performance Simulation for Challenging Surgical Tasks with Robotic Ultrasound

Ultrasound (US) is a widely used medical imaging modality due to its real-time capabilities, non-invasive nature, and cost-effectiveness. Robotic ul...

MTCNet: Motion and Topology Consistency Guided Learning for Mitral Valve Segmentationin 4D Ultrasound

Mitral regurgitation is one of the most prevalent cardiac disorders. Four-dimensional (4D) ultrasound has emerged as the primary imaging modality fo...

ADAptation: Reconstruction-based Unsupervised Active Learning for Breast Ultrasound Diagnosis

Deep learning-based diagnostic models often suffer performance drops due to distribution shifts between training (source) and test (target) domains....

Accurate and Efficient Fetal Birth Weight Estimation from 3D Ultrasound

Accurate fetal birth weight (FBW) estimation is essential for optimizing delivery decisions and reducing perinatal mortality. However, clinical meth...