Universal precautions

Adapting SAM to Nuclei Instance Segmentation and Classification via Cooperative Fine-Grained Refinement

Nuclei instance segmentation is critical in computational pathology for cancer diagnosis and prognosis. Recently, the Segment Anything Model has demonstrated exceptional performance in various segmentation tasks, leveraging its rich priors and powerful global context modeling capabilities derived from large-scale pre-training on natural images. However, directly applying SAM to the medical imaging...

RAP: Retrieve, Adapt, and Prompt-Fit for Training-Free Few-Shot Medical Image Segmentation

Few-shot medical image segmentation (FSMIS) has achieved notable progress, yet most existing methods mainly rely on semantic correspondences from scarce annotations while under-utilizing a key property of medical imagery: anatomical targets exhibit repeatable high-frequency morphology (e.g., boundary geometry and spatial layout) across patients and acquisitions. We propose RAP, a training-free fra...

Bridging Pixels and Words: Mask-Aware Local Semantic Fusion for Multimodal Media Verification

As multimodal misinformation becomes more sophisticated, its detection and grounding are crucial. However, current multimodal verification methods, re...

Federated Learning Performance Depends on Site Variation in Global HIV Data Consortia

Digital health technologies, including machine learning (ML), are transforming infectious disease management, however ML models for HIV care have been...

PMT: Plain Mask Transformer for Image and Video Segmentation with Frozen Vision Encoders

Vision Foundation Models (VFMs) pre-trained at scale enable a single frozen encoder to serve multiple downstream tasks simultaneously. Recent VFM-base...

Learning relationships in epidemiological data using graph neural networks

When designing control strategies for an infectious disease it is critical to identify the key pathways of transmission. Data on infected hosts - when...

Mitigating Objectness Bias and Region-to-Text Misalignment for Open-Vocabulary Panoptic Segmentation

Open-vocabulary panoptic segmentation remains hindered by two coupled issues: (i) mask selection bias, where objectness heads trained on closed vocabu...

From Masks to Pixels and Meaning: A New Taxonomy, Benchmark, and Metrics for VLM Image Tampering

Existing tampering detection benchmarks largely rely on object masks, which severely misalign with the true edit signal: many pixels inside a mask are...

Rethinking MLLM Itself as a Segmenter with a Single Segmentation Token

Recent segmentation methods leveraging Multi-modal Large Language Models (MLLMs) have shown reliable object-level segmentation and enhanced spatial pe...

Concept-to-Pixel: Prompt-Free Universal Medical Image Segmentation

Universal medical image segmentation seeks to use a single foundational model to handle diverse tasks across multiple imaging modalities. However, exi...

M2P: Improving Visual Foundation Models with Mask-to-Point Weakly-Supervised Learning for Dense Point Tracking

Tracking Any Point (TAP) has emerged as a fundamental tool for video understanding. Current approaches adapt Vision Foundation Models (VFMs) like DINO...

InViC: Intent-aware Visual Cues for Medical Visual Question Answering

Medical visual question answering (Med-VQA) aims to answer clinically relevant questions grounded in medical images. However, existing multimodal larg...

Rapid Bacterial Identification and Antibiotic Susceptibility Testing through Interferometry-based Surface Topography Measurement

Antimicrobial resistance poses a critical global health threat. For many bacterial infections, such as bacteremia, treatment can fail due to the time ...

DINOLight: Robust Ambient Light Normalization with Self-supervised Visual Prior Integration

This paper presents a new ambient light normalization framework, DINOLight, that integrates the self-supervised model DINOv2's image understanding cap...

Genomic streamlining of seagrass-associated Colletotrichum sp. may be related to its adaptation to a marine monocot host

Colletotrichum spp. have a complicated history of association with land plants. Perhaps most well-known as plant pathogens for the devastating effect ...

Developing Foundation Models for Universal Segmentation from 3D Whole-Body Positron Emission Tomography

Positron emission tomography (PET) is a key nuclear medicine imaging modality that visualizes radiotracer distributions to quantify in vivo physiologi...

A$^2$-Edit: Precise Reference-Guided Image Editing of Arbitrary Objects and Ambiguous Masks

We propose \textbf{A$^2$-Edit}, a unified inpainting framework for arbitrary object categories, which allows users to replace any target region with a...

SwiftTCR: Efficient Computational Docking protocol of TCRpMHC-I Complexes Using Restricted Rotation Matrices

The T cell's ability to discern self and non-self depends on its T cell receptor (TCR), which recognizes peptides presented by MHC molecules. Understa...

A Rule-Based Machine Learning Model for Predicting Virological Failure Among Children Living With HIV in Malawi

Malawi's HIV treatment monitoring system faces serious challenges because of a shortage of experts and reliance on viral load testing every 3 to 12 mo...

OccTrack360: 4D Panoptic Occupancy Tracking from Surround-View Fisheye Cameras

Understanding dynamic 3D environments in a spatially continuous and temporally consistent manner is fundamental for robotics and autonomous driving. W...