Medical Ethics / Professional Responsibility

TABNet: A Triplet Augmentation Self-Recovery Framework with Boundary-Aware Pseudo-Labels for Medical Image Segmentation

Background and objective: Medical image segmentation is a core task in various clinical applications. However, acquiring large-scale, fully annotated medical image datasets is both time-consuming and costly. Scribble annotations, as a form of sparse labeling, provide an efficient and cost-effective alternative for medical image segmentation. However, the sparsity of scribble annotations limits t...

Empowering Manufacturers with Privacy-Preserving AI Tools: A Case Study in Privacy-Preserving Machine Learning to Solve Real-World Problems

Small- and medium-sized manufacturers need innovative data tools but, because of competition and privacy concerns, often do not want to share their proprietary data with researchers who might be interested in helping. This paper introduces a privacy-preserving platform by which manufacturers may safely share their data with researchers through secure methods, so that those researchers then creat...

A Gift from the Integration of Discriminative and Diffusion-based Generative Learning: Boundary Refinement Remote Sensing Semantic Segmentation

Remote sensing semantic segmentation must address both what the ground objects are within an image and where they are located. Consequently, segment...

Mamba Guided Boundary Prior Matters: A New Perspective for Generalized Polyp Segmentation

Polyp segmentation in colonoscopy images is crucial for early detection and diagnosis of colorectal cancer. However, this task remains a significant...

Positive region preserved random sampling: an efficient feature selection method for massive data

Selecting relevant features is an important and necessary step for intelligent machines to maximize their chances of success. However, intelligent m...

Learning Boundary Continuity-Aware Gaussian Encoder for Oriented Object Detection.

Oriented object detection has been crucial for rotation-sensitive tasks and has garnered significant attention. Most existing methods generate angles ...

Rethinking boundary detection in deep learning-based medical image segmentation.

Medical image segmentation is a pivotal task within the realms of medical image analysis and computer vision. While current methods have shown promise...

Human visual perception-inspired medical image segmentation network with multi-feature compression.

Medical image segmentation is crucial for computer-aided diagnosis and treatment planning, directly influencing clinical decision-making. To enhance s...

Zero-shot 3D anomaly detection via online voter mechanism.

3D anomaly detection aims to solve the problem that image anomaly detection is greatly affected by lighting conditions. As commercial confidentiality ...

Multi-machine learning methods for rapid and synergistic inversion of groundwater contamination source, hydrogeologic parameter and boundary condition.

The application of machine learning methods to the groundwater pollution inversion problem has become a hot research topic in recent years. However, a...

PBa-LLM: Privacy- and Bias-aware NLP using Named-Entity Recognition (NER)

The use of Natural Language Processing (NLP) in highstakes AI-based applications has increased significantly in recent years, especially since the e...

MedSAM-CA: A CNN-Augmented ViT with Attention-Enhanced Multi-Scale Fusion for Medical Image Segmentation

Medical image segmentation plays a crucial role in clinical diagnosis and treatment planning, where accurate boundary delineation is essential for p...

Data-Driven Self-Supervised Learning for the Discovery of Solution Singularity for Partial Differential Equations

The appearance of singularities in the function of interest constitutes a fundamental challenge in scientific computing. It can significantly underm...

Semi Analytical Solution of a Nonlinear Oblique Boundary Value Problem

A new numerical method is developed to approximate the solution of Laplace's equation in the exterior of the sphere with a strongly nonlinear bounda...

ZKPROV: A Zero-Knowledge Approach to Dataset Provenance for Large Language Models

As the deployment of large language models (LLMs) grows in sensitive domains, ensuring the integrity of their computational provenance becomes a cri...

Personalized Mental State Evaluation in Human-Robot Interaction using Federated Learning

With the advent of Industry 5.0, manufacturers are increasingly prioritizing worker well-being alongside mass customization. Stress-aware Human-Robo...

Foundation models in pathology: bridging AI innovation and clinical practice.

Foundation models are revolutionising pathology by leveraging large-scale, pretrained artificial intelligence (AI) systems to enhance diagnostics, aut...

EVA-S2PMLP: Secure and Scalable Two-Party MLP via Spatial Transformation

Privacy-preserving neural network training in vertically partitioned scenarios is vital for secure collaborative modeling across institutions. This ...

3D Vision-tactile Reconstruction from Infrared and Visible Images for Robotic Fine-grained Tactile Perception

To achieve human-like haptic perception in anthropomorphic grippers, the compliant sensing surfaces of vision tactile sensor (VTS) must evolve from ...

Boundary-Aware Vision Transformer for Angiography Vascular Network Segmentation

Accurate segmentation of vascular structures in coronary angiography remains a core challenge in medical image analysis due to the complexity of elo...