Francesco Sforazzini

2.1k total citations · 1 hit paper
24 papers, 1.5k citations indexed

About

Francesco Sforazzini is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Francesco Sforazzini has authored 24 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Cognitive Neuroscience and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Francesco Sforazzini's work include Radiomics and Machine Learning in Medical Imaging (9 papers), Advanced MRI Techniques and Applications (8 papers) and Medical Imaging Techniques and Applications (7 papers). Francesco Sforazzini is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (9 papers), Advanced MRI Techniques and Applications (8 papers) and Medical Imaging Techniques and Applications (7 papers). Francesco Sforazzini collaborates with scholars based in Australia, Germany and Italy. Francesco Sforazzini's co-authors include Alessandro Gozzi, Angelo Bifone, Yang Zhan, Cornelius T. Gross, Laetitia Weinhard, Davide Ragozzino, Rosa Chiara Paolicelli, Giulia Bolasco, Francesca Pagani and Alexei L. Vyssotski and has published in prestigious journals such as Journal of Clinical Oncology, Nature Neuroscience and PLoS ONE.

In The Last Decade

Francesco Sforazzini

23 papers receiving 1.4k citations

Hit Papers

align trajectories sort by overperformance

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.

Deficient neuron-microglia signaling results in impaired functional brain connectivity and social behavior

2014 909 citations Yang Zhan, Rosa Chiara Paolicelli et al. Nature Neuroscience profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Francesco Sforazzini Australia	12	614	464	282	267	252	24	1.5k
Daisuke Kato Japan	16	759 1.2×	181 0.4×	453 1.6×	101 0.4×	244 1.0×	48	1.7k
Sabine Hellwig Germany	21	437 0.7×	171 0.4×	408 1.4×	240 0.9×	91 0.4×	62	1.6k
Thomas Mueggler Switzerland	20	389 0.6×	302 0.7×	368 1.3×	372 1.4×	98 0.4×	32	1.4k
Keitaro Yoshida Japan	14	267 0.4×	312 0.7×	459 1.6×	94 0.4×	61 0.2×	19	979
V.I. Rachmanova Russia	8	181 0.3×	364 0.8×	376 1.3×	398 1.5×	27 0.1×	12	1.3k
D.D. Orlovskaya Russia	16	339 0.6×	604 1.3×	739 2.6×	556 2.1×	47 0.2×	29	2.2k
Vostrikov Vm Russia	15	214 0.3×	517 1.1×	482 1.7×	479 1.8×	40 0.2×	40	1.9k
Samantha J. Fung Australia	22	284 0.5×	360 0.8×	847 3.0×	85 0.3×	56 0.2×	27	1.9k
Norbert Ulfig Germany	21	186 0.3×	259 0.6×	440 1.6×	137 0.5×	93 0.4×	76	1.4k
Jason Bruggemann Australia	20	217 0.4×	488 1.1×	135 0.5×	208 0.8×	46 0.2×	36	1.5k

Countries citing papers authored by Francesco Sforazzini

Since Specialization

Citations

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

Fields of papers citing papers by Francesco Sforazzini

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francesco Sforazzini

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

All Works

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20 of 20 papers shown

Sforazzini, Francesco, et al.. (2024). PP01.11 IMPROVED PROGNOSTIC STRATIFICATION AND RADIATIONINDUCED FIBROSIS PREDICTION AFTER STEREOTACTIC BODY RADIATION THERAPY (SBRT) FOR EARLY STAGE NON-SMALL CELL LUNG CANCER (NSCLC) VIA RADIOMICS AND DOSIOMICS. Physica Medica. 125. 103581–103581.

Sforazzini, Francesco, et al.. (2024). P10.10.B CLASSIFYING LOWER-GRADE GLIOMA SUBTYPES WITH 3D WHOLE-BRAIN MRI SCANS AND DEEP LEARNING: A NON-INVASIVE AND INTERPRETABLE APPROACH. Neuro-Oncology. 26(Supplement_5). v57–v57. 1 indexed citations

Sforazzini, Francesco, Gianluca Brugnara, Christel Herold‐Mende, et al.. (2023). MR Intensity Normalization Methods Impact Sequence Specific Radiomics Prognostic Model Performance in Primary and Recurrent High-Grade Glioma. Cancers. 15(3). 965–965. 10 indexed citations

Sforazzini, Francesco, Gianluca Brugnara, Christel Herold‐Mende, et al.. (2023). MR-Class: A Python Tool for Brain MR Image Classification Utilizing One-vs-All DCNNs to Deal with the Open-Set Recognition Problem. Cancers. 15(6). 1820–1820. 1 indexed citations

Sforazzini, Francesco, Mahmoud Moustafa, Cheng Zhou, et al.. (2022). Deep Learning–based Automatic Lung Segmentation on Multiresolution CT Scans from Healthy and Fibrotic Lungs in Mice. Radiology Artificial Intelligence. 4(2). e210095–e210095. 6 indexed citations

Sforazzini, Francesco, Laila König, Philipp Kickingereder, et al.. (2021). Improved risk stratification via integration of radiomics and dosiomics features in patients with recurrent high-grade glioma undergoing carbon ion radiotherapy (CIRT).. Journal of Clinical Oncology. 39(15_suppl). 2043–2043. 1 indexed citations

Ward, Phillip G. D., Edwina R. Orchard, Stuart Oldham, et al.. (2020). Individual differences in haemoglobin concentration influence bold fMRI functional connectivity and its correlation with cognition. NeuroImage. 221. 117196–117196. 20 indexed citations

Sforazzini, Francesco, Matthias Ülrich, Nina Bougatf, et al.. (2020). pyCuRT: An Automated Data Curation Workflow for Radiotherapy Big Data Analysis using Pythons’ NyPipe. International Journal of Radiation Oncology*Biology*Physics. 108(3). e772–e772. 2 indexed citations

Close, Thomas, et al.. (2019). A Comprehensive Framework to Capture the Arcana of Neuroimaging Analysis. Neuroinformatics. 18(1). 109–129. 1 indexed citations

10.

Sabaroedin, Kristina, Jeggan Tiego, Linden Parkes, et al.. (2019). Functional Connectivity of Corticostriatal Circuitry and Psychosis-like Experiences in the General Community. Biological Psychiatry. 86(1). 16–24. 35 indexed citations

11.

Jamadar, Sharna D., Phillip G. D. Ward, Shenpeng Li, et al.. (2019). Simultaneous task-based BOLD-fMRI and [18-F] FDG functional PET for measurement of neuronal metabolism in the human visual cortex. NeuroImage. 189. 258–266. 50 indexed citations

12.

Chen, Zhaolin, Francesco Sforazzini, Jakub Baran, et al.. (2019). MR‐PET head motion correction based on co‐registration of multicontrast MR images. Human Brain Mapping. 42(13). 4081–4091. 15 indexed citations

13.

Chen, Zhaolin, Sharna D. Jamadar, Shenpeng Li, et al.. (2018). From simultaneous to synergistic MR‐PET brain imaging: A review of hybrid MR‐PET imaging methodologies. Human Brain Mapping. 39(12). 5126–5144. 47 indexed citations

14.

Baran, Jakub, Zhaolin Chen, Francesco Sforazzini, et al.. (2018). Accurate hybrid template–based and MR-based attenuation correction using UTE images for simultaneous PET/MR brain imaging applications. BMC Medical Imaging. 18(1). 41–41. 17 indexed citations

15.

Sforazzini, Francesco, et al.. (2017). Functional subdivisions within the human intraparietal sulcus are involved in visuospatial transformation in a non‐context‐dependent manner. Human Brain Mapping. 39(1). 354–368. 9 indexed citations

16.

Errico, Francesco, Valeria D’Argenio, Francesco Sforazzini, et al.. (2015). A role for D-aspartate oxidase in schizophrenia and in schizophrenia-related symptoms induced by phencyclidine in mice. Translational Psychiatry. 5(2). e512–e512. 43 indexed citations

17.

Nicolini, Carlo, Adam Liska, Francesco Sforazzini, et al.. (2014). Modular organization of mouse brain functional connectivity. 1 indexed citations

18.

Sforazzini, Francesco, Alice Bertero, Luca Dodero, et al.. (2014). Altered functional connectivity networks in acallosal and socially impaired BTBR mice. Brain Structure and Function. 221(2). 941–954. 77 indexed citations

19.

Zhan, Yang, Rosa Chiara Paolicelli, Francesco Sforazzini, et al.. (2014). Deficient neuron-microglia signaling results in impaired functional brain connectivity and social behavior. Nature Neuroscience. 17(3). 400–406. 909 indexed citations breakdown →

20.

Sforazzini, Francesco, Adam J. Schwarz, Alberto Galbusera, Angelo Bifone, & Alessandro Gozzi. (2013). Distributed BOLD and CBV-weighted resting-state networks in the mouse brain. NeuroImage. 87. 403–415. 156 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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