Pathology

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

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Guiding the classification of hepatocellular carcinoma on 3D CT-scans using deep and handcrafted radiological features

Hepatocellular carcinoma is the most spread primary liver cancer across the world ($\sim$80\% of t...

Exploring visual language models as a powerful tool in the diagnosis of Ewing Sarcoma

Ewing's sarcoma (ES), characterized by a high density of small round blue cells without structural...

Multi-megabase scale genome interpretation with genetic language models

Understanding how molecular changes caused by genetic variation drive disease risk is crucial for ...

Lung Cancer detection using Deep Learning

In this paper we discuss lung cancer detection using hybrid model of Convolutional-Neural-Networks...

A Multi-Modal Deep Learning Framework for Pan-Cancer Prognosis

Prognostic task is of great importance as it closely related to the survival analysis of patients,...

Static Segmentation by Tracking: A Frustratingly Label-Efficient Approach to Fine-Grained Segmentation

We study image segmentation in the biological domain, particularly trait and part segmentation fro...

KeTS: Kernel-based Trust Segmentation against Model Poisoning Attacks

Federated Learning (FL) enables multiple users to collaboratively train a global model in a distri...

AI-powered virtual tissues from spatial proteomics for clinical diagnostics and biomedical discovery

Spatial proteomics technologies have transformed our understanding of complex tissue architectures...

Reusable specimen-level inference in computational pathology

Foundation models for computational pathology have shown great promise for specimen-level tasks an...

RadGPT: Constructing 3D Image-Text Tumor Datasets

With over 85 million CT scans performed annually in the United States, creating tumor-related repo...

Federated-Continual Dynamic Segmentation of Histopathology guided by Barlow Continuity

Federated- and Continual Learning have been established as approaches to enable privacy-aware lear...

Gradient Purification: Defense Against Poisoning Attack in Decentralized Federated Learning

Decentralized federated learning (DFL) is inherently vulnerable to poisoning attacks, as malicious...

GRAPHITE: Graph-Based Interpretable Tissue Examination for Enhanced Explainability in Breast Cancer Histopathology

Explainable AI (XAI) in medical histopathology is essential for enhancing the interpretability and...

Superpixel Boundary Correction for Weakly-Supervised Semantic Segmentation on Histopathology Images

With the rapid advancement of deep learning, computational pathology has made significant progress...

SELMA3D challenge: Self-supervised learning for 3D light-sheet microscopy image segmentation

Recent innovations in light sheet microscopy, paired with developments in tissue clearing techniqu...

A Value Mapping Virtual Staining Framework for Large-scale Histological Imaging

The emergence of virtual staining technology provides a rapid and efficient alternative for resear...

Enhanced Tuberculosis Bacilli Detection using Attention-Residual U-Net and Ensemble Classification

Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a critical global health issue, n...

Efficient and Accurate Tuberculosis Diagnosis: Attention Residual U-Net and Vision Transformer Based Detection Framework

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis, continues to be a m...

A One Dimensional (1D) Computational Fluid Dynamics Study of Fontan-Associated Liver Disease (FALD)

Fontan-Associated Liver Disease (FALD) is a disorder arising from hemodynamic changes and venous c...

ScaleMAI: Accelerating the Development of Trusted Datasets and AI Models

Building trusted datasets is critical for transparent and responsible Medical AI (MAI) research, b...

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