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An Effective WSSENet-Based Similarity Retrieval Method of Large Lung CT Image Databases
Open accessAbstract
With the exponential growth of medical image big data represented by high-resolution CT images(CTI), the high-resolution CTI data is of great importance for clinical research and diagnosis.The paper takes lung CTI as an example to study.Retrieving answer CTIs similar to the input one from the large-scale lung CTI database can effectively assist physicians to diagnose.Compared with the conventional content-based image retrieval(CBIR) methods, the CBIR for lung CTIs demands higher retrieval accuracy in both the contour shape and the internal details of the organ.In traditional supervised deep learning networks, the learning of the network relies on the labeling of CTIs which is a very time-consuming task.To address this issue, the paper proposes a Weakly Supervised Similarity Evaluation Network (WSSENet) for efficiently support similarity analysis of lung CTIs.We conducted extensive experiments to verify the effectiveness of the WSSENet based on which the CBIR is performed.
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“The combined metric has shown particular value in medical imaging applications [51-53].”
From A Survey and Tutorial on Image Quality Assessment with a Contrast-Weighted Structural Similarity Framework (2026) · cites this paper as [52]
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“Remote sensing: EMEE identifies small ground features and texture changes; GIA evaluates large-scale patterns and atmospheric effects. Combining these metrics can improve land-use classification accuracy and support timely applications in environmental monitoring and urban planning.”
From A Survey and Tutorial on Image Quality Assessment with a Contrast-Weighted Structural Similarity Framework (2026) · cites this paper as [52]
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“Weather monitoring: Local metrics detect cloud formation patterns; global assessment tracks large-scale weather systems and improves weather prediction model accuracy.”
From A Survey and Tutorial on Image Quality Assessment with a Contrast-Weighted Structural Similarity Framework (2026) · cites this paper as [52]
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“Diagnostic Imaging : EMEE components detect subtle tissue variations and small anatomical structures; GIA ensures that contrast and brightness levels remain clinically relevant; combined metrics assist in the early detection of pathological changes; and applications include mammography, CT scan analysis, and MRI quality assessment.”
From A Survey and Tutorial on Image Quality Assessment with a Contrast-Weighted Structural Similarity Framework (2026) · cites this paper as [52]
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“Microscopy: Local metrics evaluate cellular structure details; global assessment maintains consistent imaging conditions, particularly useful in digital pathology and cell analysis; and it is also used in satellite and aerial imaging.”
From A Survey and Tutorial on Image Quality Assessment with a Contrast-Weighted Structural Similarity Framework (2026) · cites this paper as [52]
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- Dr. Zhuang is a recipient of the CCF Doctoral Dissertation Award conferred by Chinese Computer Federation in 2008 and IBM Ph.D. Fellowship 2007-2008. From January 2008 to March 2008, supported by IBM Ph.D. Fellowship, Dr. Zhuang has spent 3 months to participate in the study of an optimal hybrid storage model based on DB2 as a research intern in IBM China Research Lab. His research interests mainly focus on multimedia database and cloud computing. He has published 40+ papers in the leading journals and conferences, i.e., ACM TOIT, TALIP, Information Sciences, KAIS, and ESWA, etc.
- Nan Jiang received the bachelor degree of medical science and the master degree of medical science both from the Zhejiang University in 2004 and 2007, respectively. Ms. Jiang is with Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine. Her research interests mainly focus on medical image processing. She has published 10+ papers in international conferences and journal.
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Agaian, S. S., Grigoryan, A. M., & Ayunts, H. (2026) · Information · doi:10.3390/info17070632
Metadata
- Authors
- Zhuang, Y., Chen, S., Jiang, N., & Hu, H.
- Affiliations
- Zhejiang Gongshang University (CN)
- Zhejiang University (CN)
- Hangzhou Normal University (CN)
- Venue
- KSII Transactions on Internet and Information Systems
- Published
- 2022-07-31
- Volume
- 16
- Issue
- 7
- ISSN
- 1976-7277 (ISSN-L)
- OpenAlex
- W4289173402
- Cited by
- 79
- References
- 5
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 19 · 2023: 57
- FWCI
- 6.38
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- KSII Transactions on Internet and Information Systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Keywords
- lung CT images, content-based image retrieval, weakly supervised learning, similarity retrieval, medical image databases
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