activity
20062024
most citedSelf-supervised Learning from 100 Million Medical Images

26 citations · 160 across the 19 of their papers we have counts for

collaborators

31 papers

eess.IV2024★ 7 cited

Deep Learning-based Unsupervised Domain Adaptation via a Unified Model for Prostate Lesion Detection Using Multisite Bi-parametric MRI Datasets

Hao Li, Han Liu, Heinrich von Busch +16

Our hypothesis is that UDA using diffusion-weighted images, generated with a unified model, offers a promising and reliable strategy for enhancing the performance of supervised lea…

cs.LG2024

Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy

Riqiang Gao, Florin C. Ghesu, Simon Arberet +5

In contemporary radiotherapy planning (RTP), a key module leaf sequencing is predominantly addressed by optimization-based approaches. In this paper, we propose a novel deep reinfo…

cs.CL2023★ 3 cited

General-Purpose vs. Domain-Adapted Large Language Models for Extraction of Structured Data from Chest Radiology Reports

Ali H. Dhanaliwala, Rikhiya Ghosh, Sanjeev Kumar Karn +4

Radiologists produce unstructured data that can be valuable for clinical care when consumed by information systems. However, variability in style limits usage. Study compares syste…

cs.CV2023

ConTrack: Contextual Transformer for Device Tracking in X-ray

Marc Demoustier, Yue Zhang, Venkatesh Narasimha Murthy +2

Device tracking is an important prerequisite for guidance during endovascular procedures. Especially during cardiac interventions, detection and tracking of guiding the catheter ti…

cs.CV2023★ 1 cited

Generation of Radiology Findings in Chest X-Ray by Leveraging Collaborative Knowledge

Manuela Daniela Danu, George Marica, Sanjeev Kumar Karn +8

Among all the sub-sections in a typical radiology report, the Clinical Indications, Findings, and Impression often reflect important details about the health status of a patient. T…

cs.CV2022★ 26 cited

Self-supervised Learning from 100 Million Medical Images

Florin C. Ghesu, Bogdan Georgescu, Awais Mansoor +8

Building accurate and robust artificial intelligence systems for medical image assessment requires not only the research and design of advanced deep learning models but also the cr…