Herng-Hua Chang

1.2k total citations
50 papers, 833 citations indexed

About

Herng-Hua Chang is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Herng-Hua Chang has authored 50 papers receiving a total of 833 indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Computer Vision and Pattern Recognition, 16 papers in Media Technology and 9 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Herng-Hua Chang's work include Medical Image Segmentation Techniques (27 papers), Image and Signal Denoising Methods (14 papers) and Advanced Image Fusion Techniques (14 papers). Herng-Hua Chang is often cited by papers focused on Medical Image Segmentation Techniques (27 papers), Image and Signal Denoising Methods (14 papers) and Advanced Image Fusion Techniques (14 papers). Herng-Hua Chang collaborates with scholars based in Taiwan, United States and Netherlands. Herng-Hua Chang's co-authors include J. Michael Fitzpatrick, Chia-Chi Sung, Daniel J. Valentino, Mao-Hsiung Chiang, Cheng‐Yuan Li, Tony W. H. Sheu, Chiu‐Wing Winnie Chu, Arthur W. Toga, Gary Duckwiler and Ming‐Chang Chiang and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Access and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Herng-Hua Chang

49 papers receiving 812 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Herng-Hua Chang Taiwan 14 468 338 143 66 65 50 833
Jianhua Yang China 13 324 0.7× 246 0.7× 100 0.7× 166 2.5× 208 3.2× 56 770
Jean‐Louis Dillenseger France 18 505 1.1× 311 0.9× 62 0.4× 269 4.1× 134 2.1× 89 979
E.-J.D. Pol Netherlands 8 461 1.0× 230 0.7× 47 0.3× 97 1.5× 49 0.8× 12 743
Tammy Riklin Raviv Israel 18 803 1.7× 225 0.7× 140 1.0× 62 0.9× 155 2.4× 44 1.2k
Petra A. van den Elsen United States 14 816 1.7× 395 1.2× 84 0.6× 167 2.5× 68 1.0× 28 1.1k
Biting Yu China 12 516 1.1× 481 1.4× 141 1.0× 180 2.7× 218 3.4× 15 998
Travis McPhail United States 4 608 1.3× 324 1.0× 40 0.3× 142 2.2× 35 0.5× 5 1.1k
Dong Hye Ye United States 17 337 0.7× 248 0.7× 34 0.2× 146 2.2× 112 1.7× 53 787
Jin Tang China 17 434 0.9× 428 1.3× 117 0.8× 203 3.1× 48 0.7× 71 1.1k
S. Kovacic Slovenia 9 721 1.5× 284 0.8× 43 0.3× 166 2.5× 92 1.4× 19 913

Countries citing papers authored by Herng-Hua Chang

Since Specialization
Citations

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

Fields of papers citing papers by Herng-Hua Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Herng-Hua Chang. 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 Herng-Hua Chang. The network helps show where Herng-Hua Chang may publish in the future.

Co-authorship network of co-authors of Herng-Hua Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Herng-Hua Chang. A scholar is included among the top collaborators of Herng-Hua Chang 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 Herng-Hua Chang. Herng-Hua Chang 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.
Chang, Herng-Hua, et al.. (2025). Underwater Image Enhancement Using Illuminant Intensity Compensation With Foreground Edge Map Rectification. IEEE Journal of Oceanic Engineering. 50(2). 835–850. 1 indexed citations
2.
Chang, Herng-Hua, et al.. (2025). Multiscale convolution block U-Net for automatic epidermis segmentation in immunofluorescence images. Biomedical Signal Processing and Control. 109. 108027–108027.
3.
Chang, Herng-Hua, et al.. (2024). Pulmonary Nodule Classification Using a Multiview Residual Selective Kernel Network. Journal of Imaging Informatics in Medicine. 37(1). 347–362. 5 indexed citations
4.
Chang, Herng-Hua, Shin‐Joe Yeh, Ming‐Chang Chiang, & Sung‐Tsang Hsieh. (2023). RU-Net: skull stripping in rat brain MR images after ischemic stroke with rat U-Net. BMC Medical Imaging. 23(1). 44–44. 5 indexed citations
5.
Chang, Herng-Hua & Cheng‐Yuan Li. (2019). An automatic restoration framework based on GPU-accelerated collateral filtering in brain MR images. BMC Medical Imaging. 19(1). 8–8. 6 indexed citations
6.
Chang, Herng-Hua, Yu-Ju Lin, & Audrey H. Zhuang. (2018). An Automatic Parameter Decision System of Bilateral Filtering with GPU-Based Acceleration for Brain MR Images. Journal of Digital Imaging. 32(1). 148–161. 10 indexed citations
7.
Chang, Herng-Hua, et al.. (2017). Brain MR Image Restoration Using an Automatic Trilateral Filter With GPU-Based Acceleration. IEEE Transactions on Biomedical Engineering. 65(2). 400–413. 14 indexed citations
8.
Chang, Herng-Hua, et al.. (2015). Automatic brain MR image denoising based on texture feature-based artificial neural networks. Bio-Medical Materials and Engineering. 26(1_suppl). S1275–82. 15 indexed citations
9.
Chang, Herng-Hua, et al.. (2015). Discrimination Ability Analysis on Texture Features for Automatic Noise Reduction in Brain MR Images. 2(1). 28–33. 1 indexed citations
10.
11.
Chang, Herng-Hua, et al.. (2014). Adaptive registration of magnetic resonance images based on a viscous fluid model. Computer Methods and Programs in Biomedicine. 117(2). 80–91. 8 indexed citations
12.
Sheu, Tony W. H., et al.. (2013). Automatic segmentation of brain MR images using an adaptive balloon snake model with fuzzy classification. Medical & Biological Engineering & Computing. 51(10). 1091–1104. 19 indexed citations
13.
Chang, Herng-Hua, et al.. (2011). Rician noise removal in MR images using an adaptive trilateral filter. 28. 467–471. 3 indexed citations
14.
Chang, Herng-Hua, Daniel J. Valentino, & Woei‐Chyn Chu. (2010). Active Shape Modeling with Electric Flows. IEEE Transactions on Visualization and Computer Graphics. 16(5). 854–869. 3 indexed citations
15.
Chang, Herng-Hua. (2010). Entropy-based trilateral filtering for noise removal in digital images. 2010 3rd International Congress on Image and Signal Processing. 18 indexed citations
16.
Chang, Herng-Hua & Chiu‐Wing Winnie Chu. (2009). Double Bilateral Filtering for Image Noise Removal. 451–455. 13 indexed citations
17.
Chang, Herng-Hua. (2008). Computer simulations of isolated conductors in electrostatic equilibrium. Physical Review E. 78(5). 56704–56704. 11 indexed citations
18.
Chang, Herng-Hua, Daniel J. Valentino, Gary Duckwiler, & Arthur W. Toga. (2007). Segmentation of Brain MR Images Using a Charged Fluid Model. IEEE Transactions on Biomedical Engineering. 54(10). 1798–1813. 18 indexed citations
19.
Chang, Herng-Hua & Daniel J. Valentino. (2007). An electrostatic deformable model for medical image segmentation. Computerized Medical Imaging and Graphics. 32(1). 22–35. 20 indexed citations
20.
Chang, Herng-Hua & J. Michael Fitzpatrick. (1992). A technique for accurate magnetic resonance imaging in the presence of field inhomogeneities. IEEE Transactions on Medical Imaging. 11(3). 319–329. 314 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Jianhua Yang Breakdown of academic impact, for papers by Jean‐Louis Dillenseger Breakdown of academic impact, for papers by E.-J.D. Pol Breakdown of academic impact, for papers by Tammy Riklin Raviv Breakdown of academic impact, for papers by Petra A. van den Elsen Breakdown of academic impact, for papers by Biting Yu Breakdown of academic impact, for papers by Travis McPhail Breakdown of academic impact, for papers by Dong Hye Ye Breakdown of academic impact, for papers by Jin Tang Breakdown of academic impact, for papers by S. Kovacic
Rankless by CCL
2026