Katja Siegmann-Luz

523 total citations · 1 hit paper
22 papers, 307 citations indexed

About

Katja Siegmann-Luz is a scholar working on Radiology, Nuclear Medicine and Imaging, Pathology and Forensic Medicine and Cancer Research. According to data from OpenAlex, Katja Siegmann-Luz has authored 22 papers receiving a total of 307 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Radiology, Nuclear Medicine and Imaging, 7 papers in Pathology and Forensic Medicine and 7 papers in Cancer Research. Recurrent topics in Katja Siegmann-Luz's work include MRI in cancer diagnosis (9 papers), Radiomics and Machine Learning in Medical Imaging (8 papers) and Breast Cancer Treatment Studies (7 papers). Katja Siegmann-Luz is often cited by papers focused on MRI in cancer diagnosis (9 papers), Radiomics and Machine Learning in Medical Imaging (8 papers) and Breast Cancer Treatment Studies (7 papers). Katja Siegmann-Luz collaborates with scholars based in Germany, Austria and Switzerland. Katja Siegmann-Luz's co-authors include Heike Preibsch, Annette Staebler, Beate Wietek, Markus Hahn, Claus D. Claussen, Sara Y. Brucker, Katharina Rall, Konstantin Nikolaou, Bernhard Krämer and Benjamin Wiesinger and has published in prestigious journals such as Nature Medicine, European Radiology and European Journal of Radiology.

In The Last Decade

Katja Siegmann-Luz

21 papers receiving 301 citations

Hit Papers

Nationwide real-world implementation of AI for cancer det... 2025 2026 2025 10 20 30 40
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Nationwide real-world implementation of AI for cancer detection in population-based mammography screening
    2025 48 citations Nora Eisemann, Trasias Mukama et al. Nature Medicine profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Katja Siegmann-Luz Germany 10 164 95 78 50 46 22 307
Xavier Caparrós Spain 7 110 0.7× 84 0.9× 94 1.2× 39 0.8× 9 0.2× 13 264
Glen Lo Australia 9 46 0.3× 58 0.6× 44 0.6× 54 1.1× 9 0.2× 26 233
A Cilotti Italy 8 327 2.0× 124 1.3× 51 0.7× 9 0.2× 30 0.7× 38 447
H.D. Zakhour United Kingdom 10 39 0.2× 134 1.4× 102 1.3× 10 0.2× 47 1.0× 22 336
Latifa Fellah Belgium 7 68 0.4× 25 0.3× 44 0.6× 47 0.9× 28 0.6× 23 193
Mari Kikuchi Japan 12 134 0.8× 120 1.3× 82 1.1× 3 0.1× 48 1.0× 37 327
Annarita Gencarelli Italy 9 58 0.4× 51 0.5× 53 0.7× 217 4.3× 38 0.8× 20 330
Lisa E. Esserman United States 10 77 0.5× 262 2.8× 163 2.1× 6 0.1× 54 1.2× 22 378
Mohiedean Ghofrani United States 11 30 0.2× 106 1.1× 74 0.9× 48 1.0× 20 0.4× 20 376
Christina Vallejo United States 7 24 0.1× 147 1.5× 100 1.3× 12 0.2× 13 0.3× 9 261

Countries citing papers authored by Katja Siegmann-Luz

Since Specialization
Citations

This map shows the geographic impact of Katja Siegmann-Luz's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Katja Siegmann-Luz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Katja Siegmann-Luz more than expected).

Fields of papers citing papers by Katja Siegmann-Luz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Katja Siegmann-Luz. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Katja Siegmann-Luz. The network helps show where Katja Siegmann-Luz may publish in the future.

Co-authorship network of co-authors of Katja Siegmann-Luz

This figure shows the co-authorship network connecting the top 25 collaborators of Katja Siegmann-Luz. A scholar is included among the top collaborators of Katja Siegmann-Luz based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Katja Siegmann-Luz. Katja Siegmann-Luz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Eisemann, Nora, Trasias Mukama, Susanne Elsner, et al.. (2025). Nationwide real-world implementation of AI for cancer detection in population-based mammography screening. Nature Medicine. 31(3). 917–924. 48 indexed citations breakdown →
2.
Wenkel, Evelyn, Eva Maria Fallenberg, Natascha Platz Batista da Silva, et al.. (2024). Recommendations of the German Radiological Society’s breast imaging working group regarding breast MRI. RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren. 196(9). 939–944. 1 indexed citations
3.
Wilpert, Caroline, Evelyn Wenkel, Pascal Baltzer, et al.. (2024). Vaccine-associated axillary lymphadenopathy with a focus on COVID-19 vaccines. RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren. 197(3). 288–297. 1 indexed citations
4.
Müller‐Schimpfle, Markus, Werner Bader, Pascal Baltzer, et al.. (2022). Konsensustreffen Mammadiagnostik 2021: Online-Austausch unter Pandemie-Bedingungen. Senologie - Zeitschrift für Mammadiagnostik und -therapie. 19(2). 127–130.
5.
Heindel, Walter, et al.. (2021). Systematische und qualitätsgesicherte Früherkennung des sporadischen Mammakarzinoms. Der Radiologe. 61(2). 126–136. 2 indexed citations
6.
7.
Müller‐Schimpfle, Markus, Werner Bader, Pascal Baltzer, et al.. (2019). Consensus Meeting of Breast Imaging: BI-RADS® and Beyond. Breast Care. 14(5). 308–314. 8 indexed citations
8.
Preibsch, Heike, et al.. (2018). Malignancy rates of B3-lesions in breast magnetic resonance imaging – do all lesions have to be excised?. BMC Medical Imaging. 18(1). 27–27. 13 indexed citations
9.
10.
Preibsch, Heike, Gunnar Blumenstock, Sara Y. Brucker, et al.. (2017). Preoperative breast MR Imaging in patients with primary breast cancer has the potential to decrease the rate of repeated surgeries. European Journal of Radiology. 94. 148–153. 8 indexed citations
11.
Preibsch, Heike, Beate Wietek, Katja Siegmann-Luz, et al.. (2015). Background parenchymal enhancement in breast MRI before and after neoadjuvant chemotherapy: correlation with tumour response. European Radiology. 26(6). 1590–1596. 61 indexed citations
12.
Preibsch, Heike & Katja Siegmann-Luz. (2015). Digitale Tomosynthese der Mamma. Der Radiologe. 55(1). 59–70. 4 indexed citations
13.
Bosse, Kristin, Claudia Ott, Thorsten Biegner, et al.. (2014). 23-Year-Old Female with an Inflammatory Myofibroblastic Tumour of the Breast: A Case Report and a Review of the Literature. Geburtshilfe und Frauenheilkunde. 74(2). 167–170. 17 indexed citations
14.
Preibsch, Heike, et al.. (2014). MR imaging-guided vacuum-assisted breast biopsy: Reduction of false-negative biopsies by short-term control MRI 24–48 h after biopsy. Clinical Radiology. 69(7). 695–702. 9 indexed citations
15.
16.
Siegmann-Luz, Katja, et al.. (2014). Abklärung ausschließlich MRT-detektierbarer Mammaläsionen. Senologie - Zeitschrift für Mammadiagnostik und -therapie. 11(2). 99–105. 1 indexed citations
17.
Siegmann-Luz, Katja. (2014). Technik und Befundung der MRT der Mamma – Das hat sich geändert. RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren. 186(S 01). 2 indexed citations
18.
Siegmann-Luz, Katja, et al.. (2013). Management of Breast Lesions Detectable Only on MRI. RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren. 186(1). 30–36. 7 indexed citations
19.
Wietek, Beate, et al.. (2013). Breast MRI of pure ductal carcinoma in situ: Sensitivity of diagnosis and influence of lesion characteristics. European Journal of Radiology. 82(10). 1731–1737. 33 indexed citations
20.
Hahn, Markus, et al.. (2013). BI-RADS® 3 lesions at contrast-enhanced breast MRI: is an initial short-interval follow-up necessary?. Acta Radiologica. 55(3). 260–265. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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