Computational Pathology

Computational pathology is an approach to diagnosis that incorporates multiple sources of data (e.g., pathology, radiology, clinical, molecular and lab operations); uses mathematical models to generate diagnostic inferences; and presents clinically actionable knowledge to customers. This vision goes beyond an informatics-centric view and leverages the core competency of pathology and the ability to effectively communicate clinically actionable knowledge. Discover the latest research on computational pahtology here.

January 20, 2021
Preprint
Open Access

Novel deep learning algorithm predicts the status of molecular pathways and key mutations in colorectal cancer from routine histology images

MedRxiv : the Preprint Server for Health Sciences
M. BilalNasir Rajpoot
December 22, 2020

The effect of quality control on accuracy of digital pathology image analysis

IEEE Journal of Biomedical and Health Informatics
Alexander I WrightDarren Treanor
November 11, 2020
Open Access

Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training

Journal of Digital Imaging
Caroline Bivik StadlerDaniel Forsberg
December 3, 2020
Review

[Technical, operational, and regulatory considerations for the adoption of digital and computational pathology].

Der Pathologe
Markus D Herrmann, Jochen Lennerz
November 17, 2020
Open Access

Roto-translation equivariant convolutional networks: Application to histopathology image analysis.

Medical Image Analysis
Maxime W LafargeM. Veta
September 18, 2020

Defining reperfusion post endovascular therapy in ischemic stroke using MR-dynamic contrast enhanced perfusion

The British Journal of Radiology
Christopher D d'EsterrePhilip A Barber
November 17, 2020

Assessment of a computerized quantitative quality control tool for kidney whole slide image biopsies

The Journal of Pathology
Yijiang ChenAndrew Janowczyk
July 17, 2020
Open Access

Enhanced prognostic stratification of neoadjuvant treated lung squamous cell carcinoma by computationally-guided tumor regression scoring

Lung Cancer : Journal of the International Association for the Study of Lung Cancer
Ruben CasanovaAlex Soltermann
December 2, 2020
Open Access

HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images.

Medical Image Analysis
Mart van RijthovenFrancesco Ciompi
August 10, 2020

NuClick: A deep learning framework for interactive segmentation of microscopic images

Medical Image Analysis
Navid Alemi KoohbananiNasir Rajpoot
November 19, 2020
Review
Open Access

Generative Adversarial Networks in Digital Pathology: A Survey on Trends and Future Potential

Patterns
Maximilian E TschuchnigMichael Gadermayr
October 13, 2020
Open Access

TissueWand, a Rapid Histopathology Annotation Tool

Journal of Pathology Informatics
Martin LindvallJonas Löwgren
September 17, 2020
Review
Open Access

Diagnostic concordance and discordance in digital pathology: a systematic review and meta-analysis

Journal of Clinical Pathology
Ayesha S AzamDavid R J Snead
December 9, 2020
Open Access

Nonlinear Image Registration and Pixel Classification Pipeline for the Study of Tumor Heterogeneity Maps

Entropy
Laura Nicolás-SáenzArrate Muñoz-Barrutia
October 10, 2020
Open Access

A Point-of-Use Quality Assurance Tool for Digital Pathology Remote Working

Journal of Pathology Informatics
Alexander I WrightDavid S Brettle
August 21, 2020
Review

Deep computational pathology in breast cancer

Seminars in Cancer Biology
Andrea DuggentoNicola Toschi

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