Elizabeth M. Hecht

6.4k total citations
128 papers, 4.6k citations indexed

About

Elizabeth M. Hecht is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Elizabeth M. Hecht has authored 128 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Radiology, Nuclear Medicine and Imaging, 36 papers in Surgery and 34 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Elizabeth M. Hecht's work include MRI in cancer diagnosis (30 papers), Advanced MRI Techniques and Applications (27 papers) and Pancreatic and Hepatic Oncology Research (23 papers). Elizabeth M. Hecht is often cited by papers focused on MRI in cancer diagnosis (30 papers), Advanced MRI Techniques and Applications (27 papers) and Pancreatic and Hepatic Oncology Research (23 papers). Elizabeth M. Hecht collaborates with scholars based in United States, Canada and France. Elizabeth M. Hecht's co-authors include James S. Babb, Vivian S. Lee, Bachir Taouli, Gary M. Israel, Glenn A. Krinsky, Daniel Kim, Samson Wong, Nicole Hindman, Steve Drew and Lorenzo Mannelli and has published in prestigious journals such as Journal of Clinical Oncology, Cancer and Radiology.

In The Last Decade

Elizabeth M. Hecht

125 papers receiving 4.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Elizabeth M. Hecht United States 34 2.7k 1.2k 909 899 771 128 4.6k
Michele Bertolotto Italy 38 1.6k 0.6× 1.4k 1.2× 2.2k 2.4× 661 0.7× 596 0.8× 209 5.5k
Maria Assunta Cova Italy 35 1.6k 0.6× 1.3k 1.1× 922 1.0× 344 0.4× 597 0.8× 199 4.3k
Eric K. Outwater United States 46 1.8k 0.7× 1.1k 0.9× 2.0k 2.2× 642 0.7× 655 0.8× 118 6.3k
Jeffrey J. Brown United States 33 1.7k 0.6× 827 0.7× 1.3k 1.4× 969 1.1× 806 1.0× 122 4.2k
Hajime Sakuma Japan 44 4.5k 1.7× 1.2k 0.9× 1.3k 1.5× 249 0.3× 589 0.8× 349 6.7k
Christine Hoeffel France 35 1.2k 0.5× 737 0.6× 2.0k 2.2× 368 0.4× 902 1.2× 209 4.5k
Shigeru Furui Japan 36 1.7k 0.6× 945 0.8× 1.5k 1.6× 789 0.9× 693 0.9× 168 4.5k
Daniel A. Merton United States 35 1.0k 0.4× 1.3k 1.0× 758 0.8× 363 0.4× 413 0.5× 123 3.5k
Daniele Marin United States 39 3.3k 1.3× 706 0.6× 700 0.8× 720 0.8× 588 0.8× 142 4.9k
Sachio Kuribayashi Japan 36 2.1k 0.8× 1.6k 1.3× 903 1.0× 385 0.4× 404 0.5× 144 4.4k

Countries citing papers authored by Elizabeth M. Hecht

Since Specialization
Citations

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

Fields of papers citing papers by Elizabeth M. Hecht

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Elizabeth M. Hecht

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

All Works

20 of 20 papers shown
1.
Fung, Alice, Brooks D. Cash, Matthew Dixon, et al.. (2025). ACR Appropriateness Criteria® Staging and Follow-Up of Primary Liver Cancer. Journal of the American College of Radiology. 22(11). S699–S712.
2.
Huang, Chenchan, Yiqiu Shen, Samuel J. Galgano, et al.. (2024). Advancements in early detection of pancreatic cancer: the role of artificial intelligence and novel imaging techniques. Abdominal Radiology. 50(4). 1731–1743. 2 indexed citations
3.
Hecht, Elizabeth M., et al.. (2024). Beyond Do No Harm: Introduction to Green Radiology. Journal of Computer Assisted Tomography. 49(2). 169–179.
4.
Huang, Chenchan, Elizabeth M. Hecht, Erik V. Soloff, et al.. (2024). Imaging for Early Detection of Pancreatic Ductal Adenocarcinoma: Updates and Challenges in the Implementation of Screening and Surveillance Programs. American Journal of Roentgenology. 223(2). e2431151–e2431151. 2 indexed citations
5.
Hentel, Keith, et al.. (2023). Patient-Centered Radiology Communications: Engaging Patients as Partners. Journal of the American College of Radiology. 21(1). 7–18. 10 indexed citations
6.
Hecht, Elizabeth M., Sherry S. Wang, Kathryn J. Fowler, et al.. (2023). Building Effective Teams in the Real World From Traps to Triumph. Journal of the American College of Radiology. 20(3). 377–384. 4 indexed citations
7.
Zulfiqar, Maria, Deyali Chatterjee, Norihide Yoneda, et al.. (2022). Imaging Features of Premalignant Biliary Lesions and Predisposing Conditions with Pathologic Correlation. Radiographics. 42(5). 1320–1337. 11 indexed citations
8.
Hecht, Elizabeth M., Giles Roditi, Christopher J. François, et al.. (2021). MR Angiography Series: Fundamentals of Contrast-enhanced MR Angiography. Radiographics. 41(4). E138–E139. 8 indexed citations
9.
Weikert, Thomas, Marco Francone, Suhny Abbara, et al.. (2020). Machine learning in cardiovascular radiology: ESCR position statement on design requirements, quality assessment, current applications, opportunities, and challenges. European Radiology. 31(6). 3909–3922. 18 indexed citations
10.
Kamath, Amita, Elizabeth M. Hecht, Claude B. Sirlin, et al.. (2019). CT/MR LI-RADS 2018: clinical implications and management recommendations. Abdominal Radiology. 44(4). 1306–1322. 26 indexed citations
11.
12.
Yacoub, Joseph H., Khaled M. Elsayes, Kathryn J. Fowler, et al.. (2018). Pitfalls in liver MRI: Technical approach to avoiding misdiagnosis and improving image quality. Journal of Magnetic Resonance Imaging. 49(1). 41–58. 14 indexed citations
13.
Kluger, Michael D., et al.. (2017). Resection of Locally Advanced Pancreatic Cancer without Regression of Arterial Encasement After Modern-Era Neoadjuvant Therapy. Journal of Gastrointestinal Surgery. 22(2). 235–241. 40 indexed citations
14.
Elsayes, Khaled M., Jonathan Hooker, Ania Z. Kielar, et al.. (2017). 2017 Version of LI-RADS for CT and MR Imaging: An Update. Radiographics. 37(7). 1994–2017. 176 indexed citations
15.
Hecht, Elizabeth M. & Andrew B. Rosenkrantz. (2009). Pulmonary MR Angiography Techniques and Applications. Magnetic Resonance Imaging Clinics of North America. 17(1). 101–131. 12 indexed citations
16.
O’Brien, James P., Monvadi B. Srichai, Elizabeth M. Hecht, Daniel Kim, & Jill E. Jacobs. (2007). Anatomy of the Heart at Multidetector CT: What the Radiologist Needs to Know. Radiographics. 27(6). 1569–1582. 45 indexed citations
17.
Israel, Gary M., Elizabeth M. Hecht, & Morton A. Bosniak. (2006). CT and MR Imaging of Complications of Partial Nephrectomy. Radiographics. 26(5). 1419–1429. 21 indexed citations
18.
Taouli, Bachir, et al.. (2006). Opposed-Phase MRI for Fat Quantification in Fat-Water Phantoms with 1H MR Spectroscopy to Resolve Ambiguity of Fat or Water Dominance. American Journal of Roentgenology. 187(1). W103–W106. 32 indexed citations
19.
Megibow, Alec J., et al.. (2006). Evaluation of Bowel Distention and Bowel Wall Appearance by Using Neutral Oral Contrast Agent for Multi–Detector Row CT. Radiology. 238(1). 87–95. 93 indexed citations
20.
Lim, Ruth, Vivian S. Lee, Genevieve L. Bennett, et al.. (2006). Imaging the Female Pelvis at 3.0 T. Topics in Magnetic Resonance Imaging. 17(6). 427–443. 6 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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