output
19992025
most citedDermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

176 citations

15 papers

q-bio.QM2025

Gut decisions based on the liver: A radiomics approach to boost colorectal cancer screening

Anna Hinterberger, Jonas Bohn, Dasha Trofimova +13

Non-invasive colorectal cancer (CRC) screening represents a key opportunity to improve colonoscopy participation rates and reduce CRC mortality. This study explores the potential o…

physics.med-ph2025

Characterization of a novel plastic scintillation detector for in vivo electron dosimetry

Cornelius J. Bauer, Frank Schneider, Ida D. Göbel +3

Introduction: Real-time dosimetry of surface doses in electron beams has not been widely established yet. Plastic scintillation detectors (PSD) promise high spatial resolution and…

cs.CV2024★ 6 cited

SynBench: A Synthetic Benchmark for Non-rigid 3D Point Cloud Registration

Sara Monji-Azad, Marvin Kinz, Claudia Scherl +3

Non-rigid point cloud registration is a crucial task in computer vision. Evaluating a non-rigid point cloud registration method requires a dataset with challenges such as large def…

eess.IV2024★ 3 cited

Deep intra-operative illumination calibration of hyperspectral cameras

Alexander Baumann, Leonardo Ayala, Alexander Studier-Fischer +6

Hyperspectral imaging (HSI) is emerging as a promising novel imaging modality with various potential surgical applications. Currently available cameras, however, suffer from poor i…

cs.LG2024★ 16 cited

AI-powered skin spectral imaging enables instant sepsis diagnosis and outcome prediction in critically ill patients

Silvia Seidlitz, Katharina Hölzl, Ayca von Garrel +10

With sepsis remaining a leading cause of mortality, early identification of patients with sepsis and those at high risk of death is a challenge of high socioeconomic importance. Gi…

cs.CL2024★ 23 cited

Superhuman performance in urology board questions by an explainable large language model enabled for context integration of the European Association of Urology guidelines: the UroBot study

Martin J. Hetz, Nicolas Carl, Sarah Haggenmüller +4

Large Language Models (LLMs) are revolutionizing medical Question-Answering (medQA) through extensive use of medical literature. However, their performance is often hampered by out…

cs.CV2024

Deep learning based detection of collateral circulation in coronary angiographies

Cosmin-Andrei Hatfaludi, Daniel Bunescu, Costin Florian Ciusdel +9

Coronary artery disease (CAD) is the dominant cause of death and hospitalization across the globe. Atherosclerosis, an inflammatory condition that gradually narrows arteries and ha…

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…

cs.CV2023★ 6 cited

Robust-DefReg: A Robust Deformable Point Cloud Registration Method based on Graph Convolutional Neural Networks

Sara Monji-Azad, Marvin Kinz, Jürgen Hesser

Point cloud registration is a fundamental problem in computer vision that aims to estimate the transformation between corresponding sets of points. Non-rigid registration, in parti…

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…

q-bio.QM2023★ 176 cited

Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

Tirtha Chanda, Katja Hauser, Sarah Hobelsberger +32

Although artificial intelligence (AI) systems have been shown to improve the accuracy of initial melanoma diagnosis, the lack of transparency in how these systems identify melanoma…

physics.med-ph2021★ 4 cited

Experimental determination of pore shapes using phase retrieval from q-space NMR diffraction

Kerstin Demberg, Frederik Bernd Laun, Marco Bertleff +2

This paper presents a novel approach on solving the phase problem in nuclear magnetic resonance (NMR) diffusion pore imaging, a method, which allows imaging the shape of arbitrary…

physics.ins-det2021★ 12 cited

A container-based facility for testing 20'000 20-inch PMTs for JUNO

Björn Wonsak, Alexander Tietzsch, Tobias Sterr +13

The main goal of the JUNO experiment is the determination of the neutrino mass ordering. To achieve this, an extraordinary energy resolution of at least at MeV is requ…

eess.IV2020★ 32 cited

Generation of annotated multimodal ground truth datasets for abdominal medical image registration

Dominik F. Bauer, Tom Russ, Barbara I. Waldkirch +5

Sparsity of annotated data is a major limitation in medical image processing tasks such as registration. Registered multimodal image data are essential for the diagnosis of medical…

cond-mat.soft1999★ 46 cited

Theory of Coherent and Incoherent Nuclear Spin-Dephasing in the Heart

Wolfgang R. Bauer, Walter Nadler, Michael Bock +4

We present an analytical theory of susceptibility induced nuclear spin dephasing in the capillary network of myocardium. Using a strong collision approach, equations are obtained f…