Pathology

Latest AI and machine learning research in pathology for healthcare professionals.

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AI-Driven Rapid Identification of Bacterial and Fungal Pathogens in Blood Smears of Septic Patients

Sepsis is a life-threatening condition which requires rapid diagnosis and treatment. Traditional m...

PERC: a suite of software tools for the curation of cryoEM data with application to simulation, modelling and machine learning

Ease of access to data, tools and models expedites scientific research. In structural biology ther...

How Good is my Histopathology Vision-Language Foundation Model? A Holistic Benchmark

Recently, histopathology vision-language foundation models (VLMs) have gained popularity due to th...

Adaptive Deep Learning for Multiclass Breast Cancer Classification via Misprediction Risk Analysis

Breast cancer remains one of the leading causes of cancer-related deaths worldwide. Early detectio...

Real-Time Cell Sorting with Scalable In Situ FPGA-Accelerated Deep Learning

Precise cell classification is essential in biomedical diagnostics and therapeutic monitoring, par...

Pathology Image Restoration via Mixture of Prompts

In digital pathology, acquiring all-in-focus images is essential to high-quality imaging and high-...

A deep learning tissue classifier based on differential co-expression genes predicts the pregnancy outcomes of cattle†.

Economic losses in cattle farms are frequently associated with failed pregnancies. Some studies foun...

Mar 2025 39832283
Cracking the PUMA Challenge in 24 Hours with CellViT++ and nnU-Net

Automatic tissue segmentation and nuclei detection is an important task in pathology, aiding in bi...

Prototype-Based Image Prompting for Weakly Supervised Histopathological Image Segmentation

Weakly supervised image segmentation with image-level labels has drawn attention due to the high c...

From Pixels to Histopathology: A Graph-Based Framework for Interpretable Whole Slide Image Analysis

The histopathological classification of whole-slide images (WSIs) is a fundamental task in digital...

Tit-for-Tat: Safeguarding Large Vision-Language Models Against Jailbreak Attacks via Adversarial Defense

Deploying large vision-language models (LVLMs) introduces a unique vulnerability: susceptibility t...

Pathology Image Compression with Pre-trained Autoencoders

The growing volume of high-resolution Whole Slide Images in digital histopathology poses significa...

Advancements in Real-Time Oncology Diagnosis: Harnessing AI and Image Fusion Techniques

Real-time computer-aided diagnosis using artificial intelligence (AI), with images, can help oncol...

Leveraging Vision-Language Embeddings for Zero-Shot Learning in Histopathology Images

Zero-shot learning holds tremendous potential for histopathology image analysis by enabling models...

Hierarchical Self-Supervised Adversarial Training for Robust Vision Models in Histopathology

Adversarial attacks pose significant challenges for vision models in critical fields like healthca...

CountPath: Automating Fragment Counting in Digital Pathology

Quality control of medical images is a critical component of digital pathology, ensuring that diag...

An Ensemble-Based Two-Step Framework for Classification of Pap Smear Cell Images

Early detection of cervical cancer is crucial for improving patient outcomes and reducing mortalit...

Patch-Wise Hypergraph Contrastive Learning with Dual Normal Distribution Weighting for Multi-Domain Stain Transfer

Virtual stain transfer leverages computer-assisted technology to transform the histochemical stain...

Multi-Modal Foundation Models for Computational Pathology: A Survey

Foundation models have emerged as a powerful paradigm in computational pathology (CPath), enabling...

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