Pathology

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

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SKOOTS: Skeleton-oriented object segmentation for mitochondria

Segmenting individual instances of mitochondria from imaging datasets can provide rich quantitative ...

Three-dimensional spatial transcriptomics at isotropic resolution enabled by generative deep learning

Mapping the complete three-dimensional (3D), transcriptome-wide spatial architecture of tissues and ...

Artificial Intelligence-driven Whole-brain Cell Mapping with Highly Multiplexed In Situ Hybridization

Recent advances in three-dimensional single-cell-resolution imaging have begun to link organ-wide an...

Single Capture Quantitative Oblique Back-Illumination Microscopy

Quantitative oblique back-illumination microscopy (qOBM) has emerged as a powerful technique for lab...

Integration of steady-state diffusion MRI with Neural Posterior Estimation (NPE) for post-mortem investigations

Post-mortem diffusion MRI plays a key role in investigative pipelines to characterise tissue microst...

Non-segmented unsupervised learning of multispectral whole slide images for robust analysis of tissue repair and regeneration

Analyzing whole tissue architecture remains challenging due to the inherent complexity of multicellu...

spEMO: Leveraging Multi-Modal Foundation Models for Analyzing Spatial Multi-Omic and Histopathology Data

Recent advances in pathology foundation models (PFMs), which are pretrained on large-scale histopath...

Cumulative microscopy reveals cellular states in fibroblasts from patients with genetic disorders

Analysis of cellular states and signaling trajectories can provide insights into causes of disease. ...

A Deep Learning Pipeline for Mapping in situ Network-level Neurovascular Coupling in Multi-photon Fluorescence Microscopy

Functional hyperaemia is a well-established hallmark of healthy brain function, whereby local brain ...

Impact of variation in tissue staining and scanning devices on performance of pan-cancer AI models: a study of sarcoma and their mimics

Histopathological analysis is considered the gold standard for the diagnosis and prognostication of ...

Deep learning-based image quantification of epithelial cell shapes and its application to polycystic kidney disease

Cell shape is a fundamental determinant of tissue architecture and organ function. In epithelial tis...

CV.eDNA: A hybrid approach to invertebrate biomonitoring using computer vision and DNA metabarcoding

Automated invertebrate classification using computer vision has shown significant potential to impro...

Influence of hyperparameters on the performance of deep learning-based microrobotic localization under phantom tissue

For the effective operation of medical microrobots within living organisms and precise targeting, it...

MR-AIV reveals in vivo brain-wide fluid flow with physics-informed AI

The circulation of cerebrospinal and interstitial fluid plays a vital role in clearing metabolic was...

MiGenPro: A linked data workflow for phenotype-genotype prediction of microbial traits using machine learning

Availability of microbial genomic data and development of machine learning methods create a unique o...

Close-Up of vesicular ER Exit Sites by Volume Electron Imaging using FIB-SEM

Volume electron microscopy by high-pressure freeze substitution combined with block-face focused ion...

Deep Learning for Molecular and Genomic Characterization of Lung Cancer in Never-Smokers Using Hematoxylin and Eosin-Stained Images

Despite promising results in using deep learning to infer genetic features from histological whole-s...

Transcriptional Signatures of Field Cancerization in Gastric Cancer

The high rate of local recurrence in gastric adenocarcinoma (GA) suggests that carcinogenesis is not...

Interpretable Deep Learning Reveals Biologically Relevant Spatial Gene Expression Patterns in Lung Tumors and their Microenvironment

Lung adenocarcinoma (LUAD), the most common subtype of non–small cell lung cancer (NSCLC) exhibits p...

Impact of Data Quality on Deep Learning Prediction of Spatial Transcriptomics from Histology Images

Spatial transcriptomics technologies enable high-throughput quantification of gene expression at spe...

Histolytics: A Panoptic Spatial Analysis Framework for Interpretable Histopathology

Quantifying spatial organization in hematoxylin and eosin (H&E)–stained whole-slide images (WSIs) is...

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