D. Schött

479 total citations
16 papers, 360 citations indexed

About

D. Schött is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Oncology. According to data from OpenAlex, D. Schött has authored 16 papers receiving a total of 360 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Biomedical Engineering and 4 papers in Oncology. Recurrent topics in D. Schött's work include Radiomics and Machine Learning in Medical Imaging (10 papers), Advanced X-ray and CT Imaging (9 papers) and Pancreatic and Hepatic Oncology Research (4 papers). D. Schött is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (10 papers), Advanced X-ray and CT Imaging (9 papers) and Pancreatic and Hepatic Oncology Research (4 papers). D. Schött collaborates with scholars based in United States, United Kingdom and China. D. Schött's co-authors include X. Allen Li, William A. Hall, Haidy Nasief, Cheng Zheng, Beth Erickson, Susan Tsai, Bradley A. Erickson, Paul Knechtges, E.S. Paulson and Kiyoko Oshima and has published in prestigious journals such as PLoS ONE, International Journal of Radiation Oncology*Biology*Physics and Medical Physics.

In The Last Decade

D. Schött

15 papers receiving 355 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. Schött United States 8 302 164 89 85 82 16 360
Haidy Nasief United States 7 297 1.0× 122 0.7× 99 1.1× 76 0.9× 99 1.2× 16 355
Sebastian Ziegelmayer Germany 13 314 1.0× 195 1.2× 111 1.2× 119 1.4× 55 0.7× 36 444
C Furstoss Canada 4 351 1.2× 56 0.3× 71 0.8× 116 1.4× 124 1.5× 9 408
May Sadik Sweden 10 407 1.3× 148 0.9× 65 0.7× 283 3.3× 149 1.8× 21 553
Juebin Jin China 12 307 1.0× 60 0.4× 49 0.6× 116 1.4× 49 0.6× 25 387
M.V. Villas Spain 5 436 1.4× 82 0.5× 68 0.8× 179 2.1× 197 2.4× 6 503
Rita Simões Netherlands 10 223 0.7× 54 0.3× 38 0.4× 87 1.0× 60 0.7× 30 309
Xiaofeng Jiang China 7 188 0.6× 111 0.7× 63 0.7× 56 0.7× 35 0.4× 13 285
Ivan Zhovannik Netherlands 8 272 0.9× 49 0.3× 69 0.8× 88 1.0× 124 1.5× 15 310
Yao Ai China 13 306 1.0× 44 0.3× 46 0.5× 119 1.4× 52 0.6× 28 378

Countries citing papers authored by D. Schött

Since Specialization
Citations

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

Fields of papers citing papers by D. Schött

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. Schött

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

All Works

16 of 16 papers shown
1.
2.
Liang, Ying, D. Schött, Zhiwu Wang, et al.. (2020). Auto-segmentation of pancreatic tumor in multi-parametric MRI using deep convolutional neural networks. Radiotherapy and Oncology. 145. 193–200. 69 indexed citations
3.
Tai, A., N Mistry, D. Schött, et al.. (2020). Improving Structure Delineation for Radiation Therapy Planning Using Dual-Energy CT. Frontiers in Oncology. 10. 1694–1694. 14 indexed citations
4.
Tai, A., et al.. (2020). Intrafractional Changes May Necessitate the Development of Real-time Adaptive Radiation Therapy for Abdominal Tumors. International Journal of Radiation Oncology*Biology*Physics. 108(3). S169–S169.
5.
Nasief, Haidy, Cheng Zheng, D. Schött, et al.. (2019). A machine learning based delta-radiomics process for early prediction of treatment response of pancreatic cancer. npj Precision Oncology. 3(1). 127 indexed citations
6.
Schött, D., Taly Gilat Schmidt, William A. Hall, et al.. (2019). Estimation of changing gross tumor volume from longitudinal CTs during radiation therapy delivery based on a texture analysis with classifier algorithms: a proof-of-concept study. Quantitative Imaging in Medicine and Surgery. 9(7). 1189–1200. 2 indexed citations
7.
8.
Schött, D., et al.. (2019). The Use of Dual-Energy CT to Eliminate the Need of Pre-Contrast CT and Registration Error for Contrast CT-Based Radiation Treatment Planning. International Journal of Radiation Oncology*Biology*Physics. 105(1). E724–E724. 1 indexed citations
9.
Liang, Ying, D. Schött, William A. Hall, et al.. (2019). On the Development of MRI-Based Auto-Segmentation of Pancreatic Tumor Using Deep Neural Networks. International Journal of Radiation Oncology*Biology*Physics. 105(1). S201–S201. 1 indexed citations
10.
Saeed, Hina, D. Schött, Ying Zhang, et al.. (2019). MRI-Based Radiomic Fingerprint in Cervical Cancer: A New Predictor for Progression-Free Survival. Brachytherapy. 18(3). S13–S13. 1 indexed citations
11.
Tai, A., D. Schött, N Mistry, et al.. (2018). Technical Note: Enhancing soft tissue contrast and radiation‐induced image changes with dual‐energy CT for radiation therapy. Medical Physics. 45(9). 4238–4245. 12 indexed citations
12.
Dalah, Entesar Z., Bradley A. Erickson, Kiyoko Oshima, et al.. (2018). Correlation of ADC With Pathological Treatment Response for Radiation Therapy of Pancreatic Cancer. Translational Oncology. 11(2). 391–398. 35 indexed citations
13.
Chen, Xiaojian, Kiyoko Oshima, D. Schött, et al.. (2017). Assessment of treatment response during chemoradiation therapy for pancreatic cancer based on quantitative radiomic analysis of daily CTs: An exploratory study. PLoS ONE. 12(6). e0178961–e0178961. 68 indexed citations
14.
15.
Schött, D., et al.. (2016). SU‐F‐R‐50: Radiation‐Induced Changes in CT Number Histogram During Chemoradiation Therapy for Pancreatic Cancer. Medical Physics. 43(6Part7). 3384–3384. 1 indexed citations
16.
Weder, B., et al.. (2000). Prediction of angiographic carotid artery stenosis indexes by colour Doppler‐assisted duplex imaging. A critical appraisal of the parameters used. European Journal of Neurology. 7(2). 183–190. 11 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Haidy Nasief Breakdown of academic impact, for papers by Sebastian Ziegelmayer Breakdown of academic impact, for papers by C Furstoss Breakdown of academic impact, for papers by May Sadik Breakdown of academic impact, for papers by Juebin Jin Breakdown of academic impact, for papers by M.V. Villas Breakdown of academic impact, for papers by Rita Simões Breakdown of academic impact, for papers by Xiaofeng Jiang Breakdown of academic impact, for papers by Ivan Zhovannik Breakdown of academic impact, for papers by Yao Ai
Rankless by CCL
2026