Heung‐Kook Choi

1.7k total citations
89 papers, 814 citations indexed

About

Heung‐Kook Choi is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Heung‐Kook Choi has authored 89 papers receiving a total of 814 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Computer Vision and Pattern Recognition, 32 papers in Radiology, Nuclear Medicine and Imaging and 31 papers in Artificial Intelligence. Recurrent topics in Heung‐Kook Choi's work include AI in cancer detection (30 papers), Radiomics and Machine Learning in Medical Imaging (24 papers) and Medical Image Segmentation Techniques (21 papers). Heung‐Kook Choi is often cited by papers focused on AI in cancer detection (30 papers), Radiomics and Machine Learning in Medical Imaging (24 papers) and Medical Image Segmentation Techniques (21 papers). Heung‐Kook Choi collaborates with scholars based in South Korea, Sweden and Sri Lanka. Heung‐Kook Choi's co-authors include Subrata Bhattacharjee, Nuwan Madusanka, Nam-Hoon Cho, Hee‐Cheol Kim, Ewert Bengtsson, Kenneth Wester, Torsten Jarkrans, Janos Vasko, Hyunju Choi and Goo‐Bo Jeong and has published in prestigious journals such as IEEE Access, RSC Advances and Journal of Clinical Pathology.

In The Last Decade

Heung‐Kook Choi

78 papers receiving 747 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Heung‐Kook Choi South Korea 16 334 259 210 140 109 89 814
Ricardo J. Ferrari Brazil 14 388 1.2× 397 1.5× 238 1.1× 106 0.8× 72 0.7× 41 764
Yongsheng Pan China 16 267 0.8× 230 0.9× 242 1.2× 142 1.0× 35 0.3× 80 1.0k
Tom Brosch Germany 10 278 0.8× 215 0.8× 288 1.4× 169 1.2× 50 0.5× 20 699
Eloy Roura Spain 11 297 0.9× 101 0.4× 208 1.0× 226 1.6× 70 0.6× 18 666
Sergi Valverde Spain 17 554 1.7× 217 0.8× 381 1.8× 448 3.2× 115 1.1× 29 1.2k
Youngjin Yoo Canada 13 228 0.7× 203 0.8× 388 1.8× 155 1.1× 60 0.6× 30 748
Alfiia Galimzianova United States 8 379 1.1× 263 1.0× 438 2.1× 354 2.5× 39 0.4× 15 1.0k
Shunxing Bao United States 14 359 1.1× 257 1.0× 472 2.2× 86 0.6× 29 0.3× 85 908
Sandra González-Villà Spain 8 278 0.8× 116 0.4× 190 0.9× 222 1.6× 51 0.5× 11 551
Dimitris Glotsos Greece 16 219 0.7× 424 1.6× 321 1.5× 114 0.8× 30 0.3× 73 868

Countries citing papers authored by Heung‐Kook Choi

Since Specialization
Citations

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

Fields of papers citing papers by Heung‐Kook Choi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Heung‐Kook Choi. 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 Heung‐Kook Choi. The network helps show where Heung‐Kook Choi may publish in the future.

Co-authorship network of co-authors of Heung‐Kook Choi

This figure shows the co-authorship network connecting the top 25 collaborators of Heung‐Kook Choi. A scholar is included among the top collaborators of Heung‐Kook Choi 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 Heung‐Kook Choi. Heung‐Kook Choi 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.
Bhattacharjee, Subrata, Myung-Jae Lee, Hee‐Cheol Kim, et al.. (2023). Region Segmentation of Whole-Slide Images for Analyzing Histological Differentiation of Prostate Adenocarcinoma Using Ensemble EfficientNetB2 U-Net with Transfer Learning Mechanism. Cancers. 15(3). 762–762. 14 indexed citations
2.
Bhattacharjee, Subrata, et al.. (2020). A Study on Deep Learning Binary Classification of Prostate Pathological Images Using Multiple Image Enhancement Techniques. Journal of Korea Multimedia Society. 23(4). 539–548. 2 indexed citations
3.
Bhattacharjee, Subrata, et al.. (2020). Multichannel Convolution Neural Network Classification for the Detection of Histological Pattern in Prostate Biopsy Images. Journal of Korea Multimedia Society. 23(12). 1486–1495. 1 indexed citations
4.
Madusanka, Nuwan, et al.. (2019). Analysis of Texture Features and Classifications for the Accurate Diagnosis of Prostate Cancer. Journal of Korea Multimedia Society. 22(8). 832–843. 3 indexed citations
5.
Al‐Shdefat, Ramadan, et al.. (2014). Semi-automated Approach to Hippocampus Segmentation Using Snake from Brain MRI. Journal of Korea Multimedia Society. 17(5). 566–572. 2 indexed citations
6.
Mun, Chi‐Woong, et al.. (2014). Implementation of 2D Active Shape Model-based Segmentation on Hippocampus. Journal of Korea Multimedia Society. 17(1). 1–7. 1 indexed citations
7.
Choi, Heung‐Kook, et al.. (2013). Comparison of Active Contour and Active Shape Approaches for Corpus Callosum Segmentation. Journal of Korea Multimedia Society. 16(9). 1018–1030. 7 indexed citations
8.
Choi, Heung‐Kook, et al.. (2013). Time Complexity Measurement on CUDA-based GPU Parallel Architecture of Morphology Operation. Journal of Korea Multimedia Society. 16(4). 444–452. 1 indexed citations
9.
Choi, Heung‐Kook, et al.. (2012). Hippocampus Volume Measurement for the determination of MCI. Journal of Korea Multimedia Society. 15(12). 1449–1455. 2 indexed citations
10.
Choi, Heung‐Kook, et al.. (2012). Contrast Enhancement for Segmentation of Hippocampus on Brain MR Images. Journal of Korea Multimedia Society. 15(12). 1409–1416. 5 indexed citations
11.
Lee, Youngseung, et al.. (2011). Computer Aided System for Breast Mass Detection and Analysis in Microwave Tomography. 318–319. 1 indexed citations
12.
Kim, Hyeon-Sik, et al.. (2009). Development of Quantification Method for Bioluminescence Imaging. Nuclear Medicine and Molecular Imaging. 43(5). 451–458.
13.
Choi, Heung‐Kook, et al.. (2009). Optimized Brightness Preserving Weight Clustering Histogram Equalization. 206–209. 1 indexed citations
14.
Choi, Heung‐Kook, et al.. (2008). Contrast Enhancement using Histogram Equalization with a New Neighborhood Metrics. Journal of Korea Multimedia Society. 11(6). 737–745. 4 indexed citations
15.
Choi, Heung‐Kook, et al.. (2007). 3D Quantitative Analysis of Cell Nuclei Based on Digital Image Cytometry. Journal of Korea Multimedia Society. 10(7). 846–855. 1 indexed citations
16.
Lee, Byeong-Il, et al.. (2006). Development of quantification software using model-based segmentation of left ventricular myocardium in gated myocardial SPECT. Computer Methods and Programs in Biomedicine. 83(1). 43–49. 1 indexed citations
17.
Choi, Heung‐Kook, Heung‐Kook Choi, Eyk Schellenberger, et al.. (2005). Quantitative Analysis of Chemotherapeutic Effects in Tumors Using In Vivo Staining and Correlative Histology. Analytical Cellular Pathology. 27(3). 183–190. 8 indexed citations
18.
Lee, Byeong-Il, Dong‐Soo Lee, Jae‐Sung Lee, et al.. (2003). Development of Evaluation Method of Regional Contractility of Left Ventricle Using Gated Myocardial SPECT and Assessment of Reproducibility. The Korean Journal of Nuclear Medicine. 37(6). 355–363. 1 indexed citations
19.
Lee, Byeong-Il, Dong‐Soo Lee, Jae-Sung Lee, et al.. (2003). Development of Gated Myocardial SPECT Analysis Software and Evaluation of Left Ventricular Contraction Function. The Korean Journal of Nuclear Medicine. 37(2). 73–82. 2 indexed citations
20.
Choi, Heung‐Kook, et al.. (2002). Tele-medical imaging conference system based on the Web. Computer Methods and Programs in Biomedicine. 68(3). 223–231. 4 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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