Oliver Schoppe

1.4k total citations
10 papers, 468 citations indexed

About

Oliver Schoppe is a scholar working on Cognitive Neuroscience, Biophysics and Biomedical Engineering. According to data from OpenAlex, Oliver Schoppe has authored 10 papers receiving a total of 468 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Cognitive Neuroscience, 3 papers in Biophysics and 3 papers in Biomedical Engineering. Recurrent topics in Oliver Schoppe's work include Neural dynamics and brain function (3 papers), Cell Image Analysis Techniques (3 papers) and Visual perception and processing mechanisms (2 papers). Oliver Schoppe is often cited by papers focused on Neural dynamics and brain function (3 papers), Cell Image Analysis Techniques (3 papers) and Visual perception and processing mechanisms (2 papers). Oliver Schoppe collaborates with scholars based in Germany, United Kingdom and Switzerland. Oliver Schoppe's co-authors include Bjoern Menze, Ali Ertürk, Mihail Ivilinov Todorov, Jan W. H. Schnupp, Andrew J. King, Ben D. B. Willmore, Nicol S. Harper, Suprosanna Shit, Johannes C. Paetzold and Marie Piraud and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and Nature Methods.

In The Last Decade

Oliver Schoppe

10 papers receiving 462 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Oliver Schoppe Germany	7	155	110	99	92	74	10	468
Suprosanna Shit Germany	10	32 0.2×	171 1.6×	91 0.9×	97 1.1×	51 0.7×	29	469
Mihail Ivilinov Todorov Germany	10	33 0.2×	120 1.1×	167 1.7×	116 1.3×	137 1.9×	15	514
Artem Khmelinskii Netherlands	9	69 0.4×	140 1.3×	30 0.3×	34 0.4×	121 1.6×	22	439
Jinling Lu China	14	112 0.7×	206 1.9×	96 1.0×	135 1.5×	198 2.7×	50	656
Bistra Iordanova United States	11	98 0.6×	278 2.5×	36 0.4×	67 0.7×	89 1.2×	24	792
Sharmishtaa Seshamani United States	10	43 0.3×	136 1.2×	241 2.4×	81 0.9×	150 2.0×	24	733
Cheng Yan China	7	90 0.6×	98 0.9×	435 4.4×	128 1.4×	159 2.1×	20	680
Julien Dauguet France	11	171 1.1×	288 2.6×	65 0.7×	58 0.6×	101 1.4×	25	756
Qingdi Wang Australia	5	55 0.4×	69 0.6×	239 2.4×	95 1.0×	95 1.3×	11	418
Dušan Ristanović Serbia	15	140 0.9×	73 0.7×	122 1.2×	56 0.6×	123 1.7×	38	578

Countries citing papers authored by Oliver Schoppe

Since Specialization

Citations

This map shows the geographic impact of Oliver Schoppe'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 Oliver Schoppe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oliver Schoppe more than expected).

Fields of papers citing papers by Oliver Schoppe

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Oliver Schoppe. 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 Oliver Schoppe. The network helps show where Oliver Schoppe may publish in the future.

Co-authorship network of co-authors of Oliver Schoppe

This figure shows the co-authorship network connecting the top 25 collaborators of Oliver Schoppe. A scholar is included among the top collaborators of Oliver Schoppe 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 Oliver Schoppe. Oliver Schoppe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

Paetzold, Johannes C., Oliver Schoppe, Ivan Ezhov, et al.. (2022). METGAN: Generative Tumour Inpainting and Modality Synthesis in Light Sheet Microscopy. 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 3230–3240. 4 indexed citations

Schoppe, Oliver, Chenchen Pan, Hongcheng Mai, et al.. (2020). Deep learning-enabled multi-organ segmentation in whole-body mouse scans. Nature Communications. 11(1). 5626–5626. 72 indexed citations

Todorov, Mihail Ivilinov, Johannes C. Paetzold, Oliver Schoppe, et al.. (2020). Machine learning analysis of whole mouse brain vasculature. Nature Methods. 17(4). 442–449. 205 indexed citations

Kimm, Melanie A., Maxim Shevtsov, Wolfgang Sievert, et al.. (2020). Gold Nanoparticle Mediated Multi-Modal CT Imaging of Hsp70 Membrane-Positive Tumors. Cancers. 12(5). 1331–1331. 29 indexed citations

Paetzold, Johannes C., Oliver Schoppe, Giles Tetteh, et al.. (2019). Transfer learning from synthetic data reduces need for labels to segment brain vasculature and neural pathways in 3D. 2 indexed citations

Schoppe, Oliver, Nicol S. Harper, Ben D. B. Willmore, Andrew J. King, & Jan W. H. Schnupp. (2016). Measuring the Performance of Neural Models. Frontiers in Computational Neuroscience. 10. 10–10. 55 indexed citations

Willmore, Ben D. B., Oliver Schoppe, Andrew J. King, Jan W. H. Schnupp, & Nicol S. Harper. (2016). Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing. Journal of Neuroscience. 36(2). 280–289. 30 indexed citations

Harper, Nicol S., Oliver Schoppe, Ben D. B. Willmore, et al.. (2016). Network Receptive Field Modeling Reveals Extensive Integration and Multi-feature Selectivity in Auditory Cortical Neurons. PLoS Computational Biology. 12(11). e1005113–e1005113. 38 indexed citations

Rudnicki, Marek, et al.. (2015). Modeling auditory coding: from sound to spikes. Cell and Tissue Research. 361(1). 159–175. 32 indexed citations

10.

Wan, Qian, Oliver Schoppe, Dónal Holland, et al.. (2013). Multifunctional Laparoscopic Trocar With Built-in Fascial Closure and Stabilization. Journal of Medical Devices. 7(3). 1 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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