Medical Ethics / Professional Responsibility

PG-SAM: Prior-Guided SAM with Medical for Multi-organ Segmentation

Segment Anything Model (SAM) demonstrates powerful zero-shot capabilities; however, its accuracy and robustness significantly decrease when applied to medical image segmentation. Existing methods address this issue through modality fusion, integrating textual and image information to provide more detailed priors. In this study, we argue that the granularity of text and the domain gap affect the ...

Enhanced Vascular Flow Simulations in Aortic Aneurysm via Physics-Informed Neural Networks and Deep Operator Networks

Due to the limited accuracy of 4D Magnetic Resonance Imaging (MRI) in identifying hemodynamics in cardiovascular diseases, the challenges in obtaining patient-specific flow boundary conditions, and the computationally demanding and time-consuming nature of Computational Fluid Dynamics (CFD) simulations, it is crucial to explore new data assimilation algorithms that offer possible alternatives to...

A Novel Channel Boosted Residual CNN-Transformer with Regional-Boundary Learning for Breast Cancer Detection

Recent advancements in detecting tumors using deep learning on breast ultrasound images (BUSI) have demonstrated significant success. Deep CNNs and ...

HiMTok: Learning Hierarchical Mask Tokens for Image Segmentation with Large Multimodal Model

The remarkable performance of large multimodal models (LMMs) has attracted significant interest from the image segmentation community. To align with...

Adaptive Transformer Attention and Multi-Scale Fusion for Spine 3D Segmentation

This study proposes a 3D semantic segmentation method for the spine based on the improved SwinUNETR to improve segmentation accuracy and robustness....

A Novel Double Pruning method for Imbalanced Data using Information Entropy and Roulette Wheel Selection for Breast Cancer Diagnosis

Accurate illness diagnosis is vital for effective treatment and patient safety. Machine learning models are widely used for cancer diagnosis based o...

Diff-CL: A Novel Cross Pseudo-Supervision Method for Semi-supervised Medical Image Segmentation

Semi-supervised learning utilizes insights from unlabeled data to improve model generalization, thereby reducing reliance on large labeled datasets....

DiffEGG: Diffusion-Driven Edge Generation as a Pixel-Annotation-Free Alternative for Instance Annotation

Achieving precise panoptic segmentation relies on pixel-wise instance annotations, but obtaining such datasets is costly. Unsupervised instance segm...

MFC 5.0: An exascale many-physics flow solver

Many problems of interest in engineering, medicine, and the fundamental sciences rely on high-fidelity flow simulation, making performant computatio...

Mitigating Hallucinations in YOLO-based Object Detection Models: A Revisit to Out-of-Distribution Detection

Object detection systems must reliably perceive objects of interest without being overly confident to ensure safe decision-making in dynamic environ...

Benchmarking Chinese Medical LLMs: A Medbench-based Analysis of Performance Gaps and Hierarchical Optimization Strategies

The evaluation and improvement of medical large language models (LLMs) are critical for their real-world deployment, particularly in ensuring accura...

Customized SAM 2 for Referring Remote Sensing Image Segmentation

Referring Remote Sensing Image Segmentation (RRSIS) aims to segment target objects in remote sensing (RS) images based on textual descriptions. Alth...

Bridge Frame and Event: Common Spatiotemporal Fusion for High-Dynamic Scene Optical Flow

High-dynamic scene optical flow is a challenging task, which suffers spatial blur and temporal discontinuous motion due to large displacement in fra...

phepy: Visual Benchmarks and Improvements for Out-of-Distribution Detectors

Applying machine learning to increasingly high-dimensional problems with sparse or biased training data increases the risk that a model is used on i...

We Care Each Pixel: Calibrating on Medical Segmentation Model

Medical image segmentation is fundamental for computer-aided diagnostics, providing accurate delineation of anatomical structures and pathological r...

Self-Supervised Large Scale Point Cloud Completion for Archaeological Site Restoration

Point cloud completion helps restore partial incomplete point clouds suffering occlusions. Current self-supervised methods fail to give high fidelit...

Calibration of the mechanical boundary conditions for a patient-specific thoracic aorta model including the heart motion effect

Objective: we propose a procedure for calibrating 4 parameters governing the mechanical boundary conditions (BCs) of a thoracic aorta (TA) model der...

Language-Assisted Feature Transformation for Anomaly Detection

This paper introduces LAFT, a novel feature transformation method designed to incorporate user knowledge and preferences into anomaly detection usin...

Autonomous Dissection in Robotic Cholecystectomy

Robotic surgery offers enhanced precision and adaptability, paving the way for automation in surgical interventions. Cholecystectomy, the gallbladde...

Boundary-Emphasized Weight Maps for Distal Airway Segmentation

Automated airway segmentation from lung CT scans is vital for diagnosing and monitoring pulmonary diseases. Despite advancements, challenges like le...