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The Langlotz Lab

The Langlotz laboratory is focused on the development and application of machine learning and other innovative computational and analytical methods to accelerate disease detection and eliminate diagnostic errors.

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Foundation Models

CheXagent: Towards a Foundation Model for Chest X-Ray Interpretation

Self-Supervised Learning

ViLLA: Fine-Grained Vision-Language Representation Learning from Real-World Data

6 CXRs showing synthetic images depicting various pathology
Generative Models

RoentGen: Vision-Language Foundation Model for Chest X-ray Generation

Radiology Report Summarization

Toward Expanding the Scope of Radiology Report Summarization to Multiple Anatomies and Modalities

Radiology Report Summarization

Overview of the RadSum23 Shared Task on Multi-modal and Multi-anatomical Radiology Report Summarization

Radiology Report Generation

Improving the Factual Correctness of Radiology Report Generation with Semantic Rewards

Knowledge graph extracted from a radiology report
Knowledge Graph Extraction

Extracting Clinical Entities and Relations to Form Knowledge Graphs from Radiology Reports

Image encoder and text encoder contrastive learning framework
Contrastive Pre-Training

Contrastive Learning of Medical Visual Representations from Paired Images and Text

Class activation maps
Computer Vision

Deep Learning to Assess Skeletal Maturity on Pediatric Hand Radiographs

Factual correctness reinforcement learning schematic
Clinical Text Summarization

Optimizing the Factual Correctness of a Summary: A Study of Summarizing Radiology Reports

Plot of synonym density vs synonym log rank
Terminology and Ontology

Expanding a radiology lexicon using contextual patterns in radiology reports

Foundational research flows
Research Policy

A Roadmap for Foundational Research on Artificial Intelligence in Medical Imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop

Table of ethics questions and responses
Data Sharing Ethics

Ethics of Using and Sharing Clinical Imaging Data for AI

The Radiology Report (Cover)
Radiology Reporting

The Radiology Report: A Guide to Thoughtful Communication for Radiologists and Other Medical Professionals