Isabel Schobert

929 total citations · 1 hit paper
18 papers, 694 citations indexed

About

Isabel Schobert is a scholar working on Hepatology, Radiology, Nuclear Medicine and Imaging and Cancer Research. According to data from OpenAlex, Isabel Schobert has authored 18 papers receiving a total of 694 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Hepatology, 12 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Cancer Research. Recurrent topics in Isabel Schobert's work include Hepatocellular Carcinoma Treatment and Prognosis (13 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and MRI in cancer diagnosis (7 papers). Isabel Schobert is often cited by papers focused on Hepatocellular Carcinoma Treatment and Prognosis (13 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and MRI in cancer diagnosis (7 papers). Isabel Schobert collaborates with scholars based in Germany, United States and Switzerland. Isabel Schobert's co-authors include Lynn Jeanette Savic, Julius Chapiro, MingDe Lin, Todd Schlachter, Charlie Alexander Hamm, James S. Duncan, Brian Letzen, Clinton J. Wang, Jeffrey C. Weinreb and Marc Ferrante and has published in prestigious journals such as Scientific Reports, Radiology and Clinical Cancer Research.

In The Last Decade

Isabel Schobert

17 papers receiving 681 citations

Hit Papers

align trajectories

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.

Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI

2019 245 citations Charlie Alexander Hamm, Clinton J. Wang et al. European Radiology profile →

Peers

Countries citing papers authored by Isabel Schobert

Since Specialization

Citations

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

Fields of papers citing papers by Isabel Schobert

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Isabel Schobert

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

All Works

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18 of 18 papers shown

#	Work	Indexed citations
1	Analyzing the TotalSegmentator for facial feature removal in head CT scans 2025 ·Radiography ·(unknown), (unknown), (unknown), (unknown), Isabel Schobert, (unknown), Robert L. Schmidt, Timo Alexander Auer, Jawed Nawabi, (unknown), (unknown), (unknown), (unknown), Charlie Alexander Hamm, Tobias Penzkofer	1
2	The established chest MRI score for cystic fibrosis can be applied to contrast agent-free matrix pencil decomposition functional MRI: a multireader analysis 2025 ·Frontiers in Medicine ·(unknown), Grzegorz Bauman, Ingo G. Steffen, Isabel Schobert, Stephanie Thee, Zulfiya Syunyaeva, Jobst Roehmel, (unknown), (unknown), (unknown), Simon Veldhoen, Oliver Bieri, Mark O. Wielpütz, Marcus Mall, Mirjam Stahl, Felix Doellinger	0
3	Is Marfan Syndrome Associated with Primary Structural Changes in the Left Atrium? 2023 ·Diagnostics ·Kun Zhang, (unknown), Isabel Schobert, (unknown), Georg Böning, Frank R. Heinzel, Leif‐Hendrik Boldt, Petra Gehle	2
4	Current Trends in Non-Invasive Imaging of Interactions in the Liver Tumor Microenvironment Mediated by Tumor Metabolism 2021 ·Cancers ·Isabel Schobert, Lynn Jeanette Savic	2
5	Comparison of metabolic and immunologic responses to transarterial chemoembolization with different chemoembolic regimens in a rabbit VX2 liver tumor model 2021 ·European Radiology ·(unknown), (unknown), Lynn Jeanette Savic, Fabian M. Laage Gaupp, (unknown), (unknown), (unknown), Isabel Schobert, Charlie Alexander Hamm, Bernhard Gebauer, John J. Walsh, (unknown), Fahmeed Hyder, MingDe Lin, David C. Madoff, Todd Schlachter, Julius Chapiro, Daniel Coman	16
6	Deep learning–assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver 2021 ·European Radiology ·(unknown), Clinton J. Wang, Lynn Jeanette Savic, Charlie Alexander Hamm, (unknown), Isabel Schobert, Bernhard Gebauer, Todd Schlachter, MingDe Lin, Jeffrey C. Weinreb, Ramesh Batra, David C. Mulligan, Xuchen Zhang, James S. Duncan, Julius Chapiro	56
7	Comparison of intrahepatic progression patterns of hepatocellular carcinoma and colorectal liver metastases following CT-guided high dose-rate brachytherapy 2021 ·Therapeutic Advances in Medical Oncology ·Xu Han, (unknown), Charlie Alexander Hamm, Isabel Schobert, (unknown), Georg Böning, (unknown), Bernd Hamm, Bernhard Gebauer, Lynn Jeanette Savic	2
8	Molecular MRI of the Immuno-Metabolic Interplay in a Rabbit Liver Tumor Model: A Biomarker for Resistance Mechanisms in Tumor-targeted Therapy? 2020 ·Radiology ·Lynn Jeanette Savic, (unknown), Isabel Schobert, Ruth R. Montgomery, Nikhil S. Joshi, John J. Walsh, (unknown), (unknown), Xuchen Zhang, MingDe Lin, (unknown), (unknown), James S. Duncan, Lin Leng, Richard Bucala, S. Nahum Goldberg, Fahmeed Hyder, Daniel Coman, Julius Chapiro	22
9	Automated detection and delineation of hepatocellular carcinoma on multiphasic contrast-enhanced MRI using deep learning 2020 ·Abdominal Radiology ·Khaled Bousabarah, Brian Letzen, (unknown), Lynn Jeanette Savic, Isabel Schobert, Todd Schlachter, Lawrence H. Staib, Martin Köcher, Julius Chapiro, MingDe Lin	64
10	Automated feature quantification of Lipiodol as imaging biomarker to predict therapeutic efficacy of conventional transarterial chemoembolization of liver cancer 2020 ·Scientific Reports ·(unknown), (unknown), Lynn Jeanette Savic, Brian Letzen, Isabel Schobert, Milena Miszczuk, (unknown), (unknown), Bernhard Gebauer, MingDe Lin, James S. Duncan, Todd Schlachter, Julius Chapiro	10
11	Neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios as predictors of tumor response in hepatocellular carcinoma after DEB-TACE 2020 ·European Radiology ·Isabel Schobert, Lynn Jeanette Savic, Julius Chapiro, Khaled Bousabarah, Evan M. Chen, Fabian M. Laage Gaupp, (unknown), Nariman Nezami, MingDe Lin, Jeffrey Pollak, Todd Schlachter	85
12	Prospective study of Lipiodol distribution as an imaging marker for doxorubicin pharmacokinetics during conventional transarterial chemoembolization of liver malignancies 2020 ·European Radiology ·Lynn Jeanette Savic, Julius Chapiro, (unknown), Khaled Bousabarah, Isabel Schobert, (unknown), Jean-François H. Geschwind, (unknown), Ping He, Michelle A. Rudek, (unknown), (unknown), Jeffrey Pollak, Todd Schlachter	8
13	A high‐throughput imaging platform to characterize extracellular pH in organotypic three‐dimensional in vitro models of liver cancer 2020 ·NMR in Biomedicine ·Lynn Jeanette Savic, Isabel Schobert, Charlie Alexander Hamm, (unknown), Fahmeed Hyder, Daniel Coman	4
14	Fluorodeoxyglucose PET for Monitoring Response to Embolotherapy (Transarterial Chemoembolization) in Primary and Metastatic Liver Tumors 2019 ·PET Clinics ·Isabel Schobert, Julius Chapiro, Darko Pucar, Lawrence Saperstein, Lynn Jeanette Savic	3
15	Quantitative Imaging Biomarkers for⁹⁰Y Distribution on Bremsstrahlung SPECT After Resin-Based Radioembolization 2019 ·Journal of Nuclear Medicine ·Isabel Schobert, Julius Chapiro, Nariman Nezami, Charlie Alexander Hamm, Bernhard Gebauer, MingDe Lin, Jeffrey Pollak, Lawrence Saperstein, Todd Schlachter, Lynn Jeanette Savic	5
16	Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI breakdown → 2019 ·European Radiology ·Charlie Alexander Hamm, Clinton J. Wang, Lynn Jeanette Savic, Marc Ferrante, Isabel Schobert, Todd Schlachter, MingDe Lin, James S. Duncan, Jeffrey C. Weinreb, Julius Chapiro, Brian Letzen	245
17	Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features 2019 ·European Radiology ·Clinton J. Wang, Charlie Alexander Hamm, Lynn Jeanette Savic, Marc Ferrante, Isabel Schobert, Todd Schlachter, MingDe Lin, Jeffrey C. Weinreb, James S. Duncan, Julius Chapiro, Brian Letzen	122
18	Molecular Imaging of Extracellular Tumor pH to Reveal Effects of Locoregional Therapy on Liver Cancer Microenvironment 2019 ·Clinical Cancer Research ·Lynn Jeanette Savic, Isabel Schobert, Dana C. Peters, John J. Walsh, (unknown), Charlie Alexander Hamm, (unknown), (unknown), MingDe Lin, Albert J. Sinusas, Todd Schlachter, James S. Duncan, Fahmeed Hyder, Daniel Coman, Julius Chapiro	47

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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