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Universal precautions

Latest AI and machine learning research in universal precautions for healthcare professionals.

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MARS: a Multimodal Alignment and Ranking System for Few-Shot Segmentation

Current Few Shot Segmentation literature lacks a mask selection method that goes beyond visual similarity between the query and example images, leading to suboptimal predictions. We present MARS, a plug-and-play ranking system that leverages multimodal cues to filter and merge mask proposals robustly. Starting from a set of mask predictions for a single query image, we score, filter, and merge t...

Virtual-mask Informed Prior for Sparse-view Dual-Energy CT Reconstruction

Sparse-view sampling in dual-energy computed tomography (DECT) significantly reduces radiation dose and increases imaging speed, yet is highly prone to artifacts. Although diffusion models have demonstrated potential in effectively handling incomplete data, most existing methods in this field focus on the image do-main and lack global constraints, which consequently leads to insufficient reconst...

S-EO: A Large-Scale Dataset for Geometry-Aware Shadow Detection in Remote Sensing Applications

We introduce the S-EO dataset: a large-scale, high-resolution dataset, designed to advance geometry-aware shadow detection. Collected from diverse p...

MedSegFactory: Text-Guided Generation of Medical Image-Mask Pairs

This paper presents MedSegFactory, a versatile medical synthesis framework that generates high-quality paired medical images and segmentation masks ...

WoundAmbit: Bridging State-of-the-Art Semantic Segmentation and Real-World Wound Care

Chronic wounds affect a large population, particularly the elderly and diabetic patients, who often exhibit limited mobility and co-existing health ...

Modular Soft Wearable Glove for Real-Time Gesture Recognition and Dynamic 3D Shape Reconstruction

With the increasing demand for human-computer interaction (HCI), flexible wearable gloves have emerged as a promising solution in virtual reality, m...

Transferable Mask Transformer: Cross-domain Semantic Segmentation with Region-adaptive Transferability Estimation

Recent advances in Vision Transformers (ViTs) have set new benchmarks in semantic segmentation. However, when adapting pretrained ViTs to new target...

URECA: Unique Region Caption Anything

Region-level captioning aims to generate natural language descriptions for specific image regions while highlighting their distinguishing features. ...

IterMask3D: Unsupervised Anomaly Detection and Segmentation with Test-Time Iterative Mask Refinement in 3D Brain MR

Unsupervised anomaly detection and segmentation methods train a model to learn the training distribution as 'normal'. In the testing phase, they ide...

Bridging Knowledge Gap Between Image Inpainting and Large-Area Visible Watermark Removal

Visible watermark removal which involves watermark cleaning and background content restoration is pivotal to evaluate the resilience of watermarks. ...

Noninvasive prediction of esophagogastric varices in hepatitis B: An extreme gradient boosting model based on ultrasound and serology.

BACKGROUND: Severe esophagogastric varices (EGVs) significantly affect prognosis of patients with hepatitis B because of the risk of life-threatening ...

Apr 7 2025 40248058
Statistical Management of the False Discovery Rate in Medical Instance Segmentation Based on Conformal Risk Control

Instance segmentation plays a pivotal role in medical image analysis by enabling precise localization and delineation of lesions, tumors, and anatom...

UCS: A Universal Model for Curvilinear Structure Segmentation

Curvilinear structure segmentation (CSS) is vital in various domains, including medical imaging, landscape analysis, industrial surface inspection, ...

BiSeg-SAM: Weakly-Supervised Post-Processing Framework for Boosting Binary Segmentation in Segment Anything Models

Accurate segmentation of polyps and skin lesions is essential for diagnosing colorectal and skin cancers. While various segmentation methods for pol...

Visually Image Encryption and Compression Using a CNN-Based Auto Encoder

This paper proposes a visual encryption method to ensure the confidentiality of digital images. The model used is based on an autoencoder using aCon...

Hybrid Global-Local Representation with Augmented Spatial Guidance for Zero-Shot Referring Image Segmentation

Recent advances in zero-shot referring image segmentation (RIS), driven by models such as the Segment Anything Model (SAM) and CLIP, have made subst...

Machine learning to improve HIV screening using routine data in Kenya.

INTRODUCTION: Optimal use of HIV testing resources accelerates progress towards ending HIV as a global threat. In Kenya, current testing practices yie...

Apr 1 2025 40254897
MuseFace: Text-driven Face Editing via Diffusion-based Mask Generation Approach

Face editing modifies the appearance of face, which plays a key role in customization and enhancement of personal images. Although much work have ac...

MGD-SAM2: Multi-view Guided Detail-enhanced Segment Anything Model 2 for High-Resolution Class-agnostic Segmentation

Segment Anything Models (SAMs), as vision foundation models, have demonstrated remarkable performance across various image analysis tasks. Despite t...

ReferDINO-Plus: 2nd Solution for 4th PVUW MeViS Challenge at CVPR 2025

Referring Video Object Segmentation (RVOS) aims to segment target objects throughout a video based on a text description. This task has attracted in...

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