M. Peroni

39 papers receiving 1.0k citations

M. Peroni's Hit Papers

Vision 20/20: Perspectives on automated image segmentation for radiotherapy 2014 · 296 citations
2960+4+8Years since publication50100150200250

Peers

M. Peroni
Comparison fields: 5 of 76
  • Radiation 574
  • Radiology, Nuclear Medicine and Imaging 404
  • Pulmonary and Respiratory Medicine 282
  • Otorhinolaryngology 30
  • Health Informatics 10
Replace Rolf Bendl with:
Rolf Bendl Germany
Hui Yan China
R. Boesecke Germany
Justin Roper United States
Rabih Hammoud United States
Anand P. Santhanam United States
Markus Stock Austria
H. Harold Li United States
Andrew Beavis United Kingdom
Günther H. Hartmann Germany
M. Peroni relative to Rolf Bendl Germany Rolf Bendl's profile →
Citations per field
00.5×3.4×
Rolf Bendl · 1×
Citations per year

Countries citing papers authored by M. Peroni

Since Specialization
Citations

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

Fields of papers citing papers by M. Peroni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside M. Peroni, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with M. Peroni Line = papers co-authored together M. Peroni links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Vision 20/20: Perspectives on automated image segmentation for radiotherapy
Hit paper breakdown →
2014296
2 2018102
3 2014102
4 201266
5 201257
6 201652
7 201744
8 202030
9 201628
10 201727
11 201826
12 201426
13 201320
14 201320
15 202016
16 201816
17 201216
18 202313
19 202012
20 201310

About M. Peroni

M. Peroni is a scholar working on Radiation, Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Biomedical Engineering, having authored 39 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (19 papers), Radiation Therapy and Dosimetry (7 papers), Medical Image Segmentation Techniques (7 papers), Medical Imaging Techniques and Applications (7 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Medical Imaging and Analysis (4 papers), Advanced Neural Network Applications (3 papers) and AI in cancer detection (3 papers). The work is most often cited by research in Radiation (574 citations), Radiology, Nuclear Medicine and Imaging (404 citations), Pulmonary and Respiratory Medicine (282 citations), Otorhinolaryngology (30 citations) and Health Informatics (10 citations). M. Peroni has collaborated with scholars based in Italy, Switzerland and United States. Frequent co-authors include G Sharp, Karl Fritscher, G. Baroni, Marco Riboldi, Vladimír Pekar, Nadya Shusharina, Harini Veeraraghavan, Jinzhong Yang, Maria Francesca Spadea and Antony Lomax. Their work appears in journals such as Medical Physics, Radiotherapy and Oncology, Physics in Medicine and Biology, Technology in Cancer Research & Treatment and International Journal of Radiation Oncology*Biology*Physics.

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