Pathology

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

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Adaptation of Weakly Supervised Localization in Histopathology by Debiasing Predictions

Weakly Supervised Object Localization (WSOL) models enable joint classification and region-of-intere...

DeepHistoViT: An Interpretable Vision Transformer Framework for Histopathological Cancer Classification

Histopathology remains the gold standard for cancer diagnosis because it provides detailed cellular-...

OrthoEraser: Coupled-Neuron Orthogonal Projection for Concept Erasure

Text-to-image (T2I) models face significant safety risks from adversarial induction, yet current con...

Automated Detection of Malignant Lesions in the Ovary Using Deep Learning Models and XAI

The unrestrained proliferation of cells that are malignant in nature is cancer. In recent times, med...

Cross-Attention Enables Context-Aware Multimodal Skin Lesion Diagnosis

Clinical diagnosis of skin lesions integrates visual dermoscopic features with patient context such ...

Transformer-Based Multi-Region Segmentation and Radiomic Analysis of HR-pQCT Imaging for Osteoporosis Classification

Osteoporosis is a skeletal disease typically diagnosed using dual-energy X-ray absorptiometry (DXA),...

Transformer-Based Multi-Region Segmentation and Radiomic Analysis of HR-pQCT Imaging

Osteoporosis is a skeletal disease typically diagnosed using dual-energy X-ray absorptiometry (DXA),...

MIL-PF: Multiple Instance Learning on Precomputed Features for Mammography Classification

Modern foundation models provide highly expressive visual representations, yet adapting them to high...

MUSA-PINN: Multi-scale Weak-form Physics-Informed Neural Networks for Fluid Flow in Complex Geometries

While Physics-Informed Neural Networks (PINNs) offer a mesh-free approach to solving PDEs, standard ...

PathoScribe: Transforming Pathology Data into a Living Library with a Unified LLM-Driven Framework for Semantic Retrieval and Clinical Integration

Pathology underpins modern diagnosis and cancer care, yet its most valuable asset, the accumulated e...

A general methodology for liver sinusoid fenestration analysis based on 3D electron microscopy data

The liver has a complex architecture composed of millions of lobules. Within these lobules, hepatocy...

MINT: Molecularly Informed Training with Spatial Transcriptomics Supervision for Pathology Foundation Models

Pathology foundation models learn morphological representations through self-supervised pretraining ...

Beyond Attention Heatmaps: How to Get Better Explanations for Multiple Instance Learning Models in Histopathology

Multiple instance learning (MIL) has enabled substantial progress in computational histopathology, w...

Rectified flow-based prediction of post-treatment brain MRI from pre-radiotherapy priors for patients with glioma

Purpose/Objective: Brain tumors result in 20 years of lost life on average. Standard therapies induc...

MUSA-PINN: Multi-scale Weak-form Physics-Informed Neural Networks for Fluid Flow in Complex Geometries

While Physics-Informed Neural Networks (PINNs) offer a mesh-free approach to solving PDEs, standard ...

DECADE: A Temporally-Consistent Unsupervised Diffusion Model for Enhanced Rb-82 Dynamic Cardiac PET Image Denoising

Rb-82 dynamic cardiac PET imaging is widely used for the clinical diagnosis of coronary artery disea...

TumorChain: Interleaved Multimodal Chain-of-Thought Reasoning for Traceable Clinical Tumor Analysis

Accurate tumor analysis is central to clinical radiology and precision oncology, where early detecti...

BlackMirror: Black-Box Backdoor Detection for Text-to-Image Models via Instruction-Response Deviation

This paper investigates the challenging task of detecting backdoored text-to-image models under blac...

CRIMSON: A Clinically-Grounded LLM-Based Metric for Generative Radiology Report Evaluation

We introduce CRIMSON, a clinically grounded evaluation framework for chest X-ray report generation t...

SpaCRD: Multimodal Deep Fusion of Histology and Spatial Transcriptomics for Cancer Region Detection

Accurate detection of cancer tissue regions (CTR) enables deeper analysis of the tumor microenvironm...

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