output
20132026
most citedDetecting and interpreting myocardial infarction using fully convolutional neural networks

176 citations

Showing eess.IVShow all

5 papers · 1 filter

eess.IV2024★ 17 cited

FedSynthCT-Brain: A Federated Learning Framework for Multi-Institutional Brain MRI-to-CT Synthesis

Ciro Benito Raggio, Mathias Krohmer Zabaleta, Nils Skupien +6

The generation of Synthetic Computed Tomography (sCT) images has become a pivotal methodology in modern clinical practice, particularly in the context of Radiotherapy (RT) treatmen…

eess.IV2024★ 34 cited

Clinical Melanoma Diagnosis with Artificial Intelligence: Insights from a Prospective Multicenter Study

Lukas Heinlein, Roman C. Maron, Achim Hekler +27

Early detection of melanoma, a potentially lethal type of skin cancer with high prevalence worldwide, improves patient prognosis. In retrospective studies, artificial intelligence…

eess.IV2023★ 8 cited

Using Multiple Dermoscopic Photographs of One Lesion Improves Melanoma Classification via Deep Learning: A Prognostic Diagnostic Accuracy Study

Achim Hekler, Roman C. Maron, Sarah Haggenmüller +28

Background: Convolutional neural network (CNN)-based melanoma classifiers face several challenges that limit their usefulness in clinical practice. Objective: To investigate the im…

eess.IV2019

Spatio-Temporal Deep Learning Models for Tip Force Estimation During Needle Insertion

Nils Gessert, Torben Priegnitz, Thore Saathoff +6

Purpose. Precise placement of needles is a challenge in a number of clinical applications such as brachytherapy or biopsy. Forces acting at the needle cause tissue deformation and…

eess.IV2018★ 2 cited

An Analysis by Synthesis Approach for Automatic Vertebral Shape Identification in Clinical QCT

Stefan Reinhold. Timo Damm, Lukas Huber, Reimer Andresen +3

Quantitative computed tomography (QCT) is a widely used tool for osteoporosis diagnosis and monitoring. The assessment of cortical markers like cortical bone mineral density (BMD)…