Jianming Liang

Assoc Professor

  • 1533 Citations
  • 17 h-Index
19972020
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Personal profile

Education/Academic qualification

Computer Science, PHD, Turku Centre for Computer Science

… → 2001

Computer Science, MS, North China Institute of Computing Technology

… → 1990

Computer Science, BS, University of Science and Technology

… → 1987

Fingerprint Dive into the research topics where Jianming Liang is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Image analysis Engineering & Materials Science
Pulmonary Embolism Medicine & Life Sciences
Polyps Medicine & Life Sciences
Neural networks Engineering & Materials Science
Angiography Engineering & Materials Science
Colonoscopy Medicine & Life Sciences
Computer-aided Detection Mathematics
Lung Medicine & Life Sciences

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 1997 2019

Computer-aided detection and visualization of pulmonary embolism using a novel, compact, and discriminative image representation

Tajbakhsh, N., Shin, J. Y., Gotway, M. B. & Liang, J., Dec 2019, In : Medical image analysis. 58, 101541.

Research output: Contribution to journalArticle

Pulmonary Embolism
Visualization
Computer aided design
Defects
Crops

Models genesis: generic autodidactic models for 3d medical image analysis

Zhou, Z., Sodha, V., Rahman Siddiquee, M. M., Feng, R., Tajbakhsh, N., Gotway, M. B. & Liang, J., Jan 1 2019, Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings. Shen, D., Yap, P-T., Liu, T., Peters, T. M., Khan, A., Staib, L. H., Essert, C. & Zhou, S. (eds.). Springer, p. 384-393 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11767 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Medical Image Analysis
3D Image
Image analysis
Model
Transfer Learning
3 Citations (Scopus)

Surrogate supervision for medical image analysis: Effective deep learning from limited quantities of labeled data

Tajbakhsh, N., Hu, Y., Cao, J., Yan, X., Xiao, Y., Lu, Y., Liang, J., Terzopoulos, D. & Ding, X., Apr 2019, ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, p. 1251-1255 5 p. 8759553. (Proceedings - International Symposium on Biomedical Imaging; vol. 2019-April).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Image analysis
Learning
Medical imaging
Neural Networks (Computer)
Diagnostic Imaging
1 Citation (Scopus)

An ensemble of convolutional neural networks for the use in video endoscopy

Aksenov, S. V., Kostin, K. A., Ivanova, A. V., Liang, J. & Zamyatin, A. V., Jan 1 2018, In : Sovremennye Tehnologii v Medicine. 10, 2, p. 7-17 11 p.

Research output: Contribution to journalArticle

Endoscopy
Neural networks
Classifiers
Neural Networks (Computer)
Colonoscopy
1 Citation (Scopus)

Integrating Active Learning and Transfer Learning for Carotid Intima-Media Thickness Video Interpretation

Zhou, Z., Shin, J., Feng, R., Hurst, R. T., Kendall, C. B. & Liang, J., Jan 1 2018, (Accepted/In press) In : Journal of Digital Imaging.

Research output: Contribution to journalArticle

Carotid Intima-Media Thickness
Problem-Based Learning
Tuning
Neural networks
Ultrasonography

Projects 2010 2020