Jianming Liang

21.6k total citations · 4 hit papers
89 papers, 12.8k citations indexed

About

Jianming Liang is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jianming Liang has authored 89 papers receiving a total of 12.8k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Radiology, Nuclear Medicine and Imaging, 29 papers in Artificial Intelligence and 28 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jianming Liang's work include AI in cancer detection (20 papers), COVID-19 diagnosis using AI (18 papers) and Radiomics and Machine Learning in Medical Imaging (17 papers). Jianming Liang is often cited by papers focused on AI in cancer detection (20 papers), COVID-19 diagnosis using AI (18 papers) and Radiomics and Machine Learning in Medical Imaging (17 papers). Jianming Liang collaborates with scholars based in United States, China and Germany. Jianming Liang's co-authors include Nima Tajbakhsh, Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Suryakanth Gurudu, Michael B. Gotway, J. Shin, R. Todd Hurst, Christopher B. Kendall, Mohammad Reza Hosseinzadeh Taher and K. R. Gurney and has published in prestigious journals such as Nature, Nature Communications and Environmental Science & Technology.

In The Last Decade

Jianming Liang

84 papers receiving 12.6k 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.

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

2018 5.3k citations Zongwei Zhou, Nima Tajbakhsh et al. Lecture notes in computer science profile →
UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation

2019 2.6k citations Zongwei Zhou, Nima Tajbakhsh et al. IEEE Transactions on Medical Imaging profile →
Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?

2016 2.1k citations Nima Tajbakhsh, J. Shin et al. IEEE Transactions on Medical Imaging profile →
Automated Polyp Detection in Colonoscopy Videos Using Shape and Context Information

2015 644 citations Nima Tajbakhsh, Suryakanth Gurudu et al. IEEE Transactions on Medical Imaging profile →

Peers

Jianming Liang

CVPR

RNMI

ONCOL

Nima Tajbakhsh United States

Zongwei Zhou United States

Hao Chen China

Md Mahfuzur Rahman Siddiquee United States

Jing Qin China

Karthikeyan Shanmugam United States

Pheng‐Ann Heng Hong Kong

I. Dinstein Israel

Xiaojuan Qi China

Le Lü United States

Nima Tajbakhsh United States

Jianming Liang

5.4k ×1.0

CVPR

4.8k ×1.0

RNMI

4.1k ×1.0

1.5k ×1.0

1.2k ×0.9

ONCOL

Citations per year, relative to Jianming Liang Jianming Liang (= 1×) peers Nima Tajbakhsh

Countries citing papers authored by Jianming Liang

Since Specialization

Citations

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

Fields of papers citing papers by Jianming Liang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jianming Liang

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Gotway, Michael B., et al.. (2025). A fully open AI foundation model applied to chest radiography. Nature. 643(8071). 488–498. 1 indexed citations

Taher, Mohammad Reza Hosseinzadeh, Fatemeh Haghighi, Michael B. Gotway, & Jianming Liang. (2025). Large-scale benchmarking and boosting transfer learning for medical image analysis. Medical Image Analysis. 102. 103487–103487. 4 indexed citations

Zhou, Xin, Qing Chen, Haiping Jiang, et al.. (2025). Clinical and Radiographic Outcomes of Atlantoaxial or Occipitocervical Fixation and Fusion in Patients With Cervical Myelopathy due to Idiopathic Retro-Odontoid Pseudotumor. Operative Neurosurgery. 29(1). 102–108.

Pitt, Joseph, Israel Lopez‐Coto, A. Karion, et al.. (2024). Underestimation of Thermogenic Methane Emissions in New York City. Environmental Science & Technology. 58(21). 9147–9157. 5 indexed citations

Haghighi, Fatemeh, Mohammad Reza Hosseinzadeh Taher, Michael B. Gotway, & Jianming Liang. (2024). Self-supervised learning for medical image analysis: Discriminative, restorative, or adversarial?. Medical Image Analysis. 94. 103086–103086. 11 indexed citations

Taher, Mohammad Reza Hosseinzadeh, Michael B. Gotway, & Jianming Liang. (2024). Representing Part-Whole Hierarchies in Foundation Models by Learning Localizability, Composability, and Decomposability from Anatomy via Self-Supervision. PubMed. abs/210504906(2024). 11269–11281. 3 indexed citations

Gotway, Michael B., et al.. (2024). Stepwise incremental pretraining for integrating discriminative, restorative, and adversarial learning. Medical Image Analysis. 95. 103159–103159. 5 indexed citations

Taher, Mohammad Reza Hosseinzadeh, Michael B. Gotway, & Jianming Liang. (2023). Towards Foundation Models Learned from Anatomy in Medical Imaging via Self-supervision. Lecture notes in computer science. 14293. 94–104. 9 indexed citations

Zhou, Zongwei, et al.. (2023). Seeking an optimal approach for Computer-aided Diagnosis of Pulmonary Embolism. Medical Image Analysis. 91. 102988–102988. 13 indexed citations

10.

Gotway, Michael B., et al.. (2022). Discriminative, Restorative, and Adversarial Learning: Stepwise Incremental Pretraining. Lecture notes in computer science. 13542. 66–76. 6 indexed citations

11.

Haghighi, Fatemeh, et al.. (2022). POPAR: Patch Order Prediction and Appearance Recovery for Self-supervised Medical Image Analysis. Lecture notes in computer science. 13542. 77–87. 5 indexed citations

12.

Gurney, K. R., Jianming Liang, Geoffrey Roest, et al.. (2021). Under-reporting of greenhouse gas emissions in U.S. cities. Nature Communications. 12(1). 553–553. 112 indexed citations

13.

Taher, Mohammad Reza Hosseinzadeh, Fatemeh Haghighi, Ruibin Feng, Michael B. Gotway, & Jianming Liang. (2021). A Systematic Benchmarking Analysis of Transfer Learning for Medical Image Analysis. Lecture notes in computer science. 12968. 3–13. 26 indexed citations

14.

Miles, N. L., K. J. Davis, Scott J. Richardson, et al.. (2021). The influence of near-field fluxes on seasonal carbon dioxide enhancements: results from the Indianapolis Flux Experiment (INFLUX). Carbon Balance and Management. 16(1). 4–4. 10 indexed citations

15.

Liang, Jianming, Qi Wang, & Jingya Wang. (2021). Evaluation of the influence of "Internet+" hand hygiene management model on medical staff's hand hygiene compliance. Minerva Surgery. 78(2). 214–216. 1 indexed citations

16.

Feng, Ruibin, Zongwei Zhou, Michael B. Gotway, & Jianming Liang. (2020). Parts2Whole: Self-supervised Contrastive Learning via Reconstruction. Lecture notes in computer science. 12444. 85–95. 11 indexed citations

17.

Tajbakhsh, Nima, J. Shin, Michael B. Gotway, & Jianming Liang. (2019). Computer-aided detection and visualization of pulmonary embolism using a novel, compact, and discriminative image representation. Medical Image Analysis. 58. 101541–101541. 44 indexed citations

18.

Tajbakhsh, Nima, J. Shin, Suryakanth Gurudu, et al.. (2016). Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?. IEEE Transactions on Medical Imaging. 35(5). 1299–1312. 2079 indexed citations breakdown →

19.

Das, Marco, Georg Mühlenbruch, Annemarie Bakai, et al.. (2008). Computer-aided detection of pulmonary embolism: Influence on radiologists’ detection performance with respect to vessel segments. European Radiology. 18(7). 1350–1355. 43 indexed citations

20.

Bogoni, Luca, Pascal Cathier, Murat Dündar, et al.. (2005). Computer-aided detection (CAD) for CT colonography: a tool to address a growing need. British Journal of Radiology. 78(suppl_1). S57–S62. 56 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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