Yu-Len Huang

1.5k total citations
60 papers, 1.1k citations indexed

About

Yu-Len Huang is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yu-Len Huang has authored 60 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Radiology, Nuclear Medicine and Imaging, 26 papers in Artificial Intelligence and 23 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yu-Len Huang's work include AI in cancer detection (24 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Ultrasound Imaging and Elastography (11 papers). Yu-Len Huang is often cited by papers focused on AI in cancer detection (24 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Ultrasound Imaging and Elastography (11 papers). Yu-Len Huang collaborates with scholars based in Taiwan, China and South Korea. Yu-Len Huang's co-authors include Dar‐Ren Chen, Ruey‐Feng Chang, Wu‐Chung Shen, Kao-Lun Wang, Jeon‐Hor Chen, Tsu‐Yi Hsieh, Shou‐Jen Kuo, Hwa‐Koon Wu, Yi‐Hsuan Hsiao and Chia-Jen Chang and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Image Processing and Physics in Medicine and Biology.

In The Last Decade

Yu-Len Huang

59 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yu-Len Huang Taiwan 17 566 485 480 143 115 60 1.1k
Juan Shan United States 15 888 1.6× 786 1.6× 621 1.3× 195 1.4× 95 0.8× 42 1.6k
Olcay Sertel United States 18 882 1.6× 338 0.7× 637 1.3× 56 0.4× 97 0.8× 26 1.2k
Lena Costaridou Greece 18 715 1.3× 850 1.8× 506 1.1× 130 0.9× 75 0.7× 86 1.5k
Dibendu Betal United Kingdom 11 764 1.3× 360 0.7× 571 1.2× 78 0.5× 148 1.3× 29 1.2k
Chung‐Ming Lo Taiwan 21 564 1.0× 746 1.5× 284 0.6× 53 0.4× 68 0.6× 62 1.2k
Shichong Zhou China 18 597 1.1× 813 1.7× 229 0.5× 58 0.4× 153 1.3× 63 1.4k
Korsuk Sirinukunwattana United Kingdom 16 1.6k 2.8× 1.1k 2.2× 969 2.0× 124 0.9× 165 1.4× 38 2.2k
Dimitris Samaras United States 12 684 1.2× 427 0.9× 422 0.9× 46 0.3× 81 0.7× 28 1.0k
Michał Byra Poland 15 723 1.3× 817 1.7× 220 0.5× 51 0.4× 63 0.5× 42 1.3k

Countries citing papers authored by Yu-Len Huang

Since Specialization
Citations

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

Fields of papers citing papers by Yu-Len Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yu-Len Huang. 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 Yu-Len Huang. The network helps show where Yu-Len Huang may publish in the future.

Co-authorship network of co-authors of Yu-Len Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Yu-Len Huang. A scholar is included among the top collaborators of Yu-Len Huang 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 Yu-Len Huang. Yu-Len Huang 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.
Lee, Chia‐Fen, Joseph Lin, Yu-Len Huang, et al.. (2025). Deep learning-based breast MRI for predicting axillary lymph node metastasis: a systematic review and meta-analysis. Cancer Imaging. 25(1). 44–44. 1 indexed citations
2.
Chang, Chia-Jen, et al.. (2021). Automatic Segmentation of Choroid Layer Using Deep Learning on Spectral Domain Optical Coherence Tomography. Applied Sciences. 11(12). 5488–5488. 14 indexed citations
3.
Shia, Wei-Chung, et al.. (2018). Mammographic Density Distribution of Healthy Taiwanese Women and its Naturally Decreasing Trend with Age. Scientific Reports. 8(1). 14937–14937. 5 indexed citations
4.
5.
Shia, Wei-Chung, Hwa‐Koon Wu, Shih-Lung Lin, et al.. (2018). Implant volume estimation in direct-to-implant breast reconstruction after nipple-sparing mastectomy. Journal of Surgical Research. 231. 290–296. 8 indexed citations
6.
Shia, Wei-Chung, Yu-Len Huang, Hwa‐Koon Wu, & Dar‐Ren Chen. (2017). Using Flow Characteristics in Three-Dimensional Power Doppler Ultrasound Imaging to Predict Complete Responses in Patients Undergoing Neoadjuvant Chemotherapy. Journal of Ultrasound in Medicine. 36(5). 887–900. 7 indexed citations
7.
Kuo, Shou‐Jen, et al.. (2014). Stellate Masses and Histologic Grades in Breast Cancer. Ultrasound in Medicine & Biology. 40(5). 904–916. 4 indexed citations
8.
Huang, Yu-Len, et al.. (2013). Three-Dimensional Region-Based Segmentation for Breast Tumors on Sonography. Journal of Ultrasound in Medicine. 32(5). 835–846. 7 indexed citations
9.
Tsai, I‐Chen, Yu-Len Huang, & Kai‐Hua Kuo. (2011). Left ventricular myocardium segmentation on arterial phase of multi-detector row computed tomography. Computerized Medical Imaging and Graphics. 36(1). 25–37. 4 indexed citations
10.
Huang, Yu-Len, et al.. (2008). Adaptive Automatic Segmentation of HEp-2 Cells in Indirect Immunofluorescence Images. 418–422. 31 indexed citations
11.
Huang, Yu-Len, et al.. (2006). Temporal Error Concealment for MPEG-Coded Video over Error-Prone Networks. 網際網路技術學刊. 7(4). 427–432. 2 indexed citations
12.
Huang, Yu-Len, et al.. (2006). Evaluation of image compression for computer-aided diagnosis of breast tumors in 3D sonography. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6147. 614701–614701. 3 indexed citations
13.
Huang, Yu-Len. (2005). A fast method for textural analysis of DCT-based image. Journal of information science and engineering. 21(1). 181–194. 9 indexed citations
14.
Huang, Yu-Len & Dar‐Ren Chen. (2004). Watershed segmentation for breast tumor in 2-D sonography. Ultrasound in Medicine & Biology. 30(5). 625–632. 148 indexed citations
15.
Huang, Yu-Len & Ruey‐Feng Chang. (2004). A Fast Finite-State Algorithm for Generating RGB Palettes of Color Quantized Images.. Journal of information science and engineering. 20. 771–782. 13 indexed citations
16.
Huang, Yu-Len, Jeon‐Hor Chen, & Wu‐Chung Shen. (2004). Computer-Aided Dianosis of Liver Tumors in Non-Enganced CT Images. 9(3). 141–150. 5 indexed citations
17.
Huang, Yu-Len. (2004). Wavelet-based image interpolation using multilayer perceptrons. Neural Computing and Applications. 14(1). 1–10. 17 indexed citations
18.
Chang, Ruey‐Feng, et al.. (2000). Automatic Facial Feature Extraction in Model-Based Coding.. Journal of information science and engineering. 16. 447–458. 10 indexed citations
19.
Chen, Dar‐Ren, et al.. (2000). Texture analysis of breast tumors on sonograms. Seminars in Ultrasound CT and MRI. 21(4). 308–316. 45 indexed citations
20.
Chang, Ruey‐Feng & Yu-Len Huang. (1994). <title>Subband finite-state vector quantization</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 2308. 177–188. 1 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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