Etsuo Takada

656 total citations
33 papers, 468 citations indexed

About

Etsuo Takada is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Etsuo Takada has authored 33 papers receiving a total of 468 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 18 papers in Radiology, Nuclear Medicine and Imaging and 10 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Etsuo Takada's work include AI in cancer detection (19 papers), Ultrasound Imaging and Elastography (8 papers) and Breast Lesions and Carcinomas (5 papers). Etsuo Takada is often cited by papers focused on AI in cancer detection (19 papers), Ultrasound Imaging and Elastography (8 papers) and Breast Lesions and Carcinomas (5 papers). Etsuo Takada collaborates with scholars based in Japan, Taiwan and South Korea. Etsuo Takada's co-authors include Tokiko Endo, Ruey‐Feng Chang, Takako Morita, Hiroshi Fujita, Takeshi Hara, Daisuke Fukuoka, Kiyoka Omoto, Toshikazu Ito, Yukio Miyamoto and Chiun‐Sheng Huang and has published in prestigious journals such as American Journal of Roentgenology, Medical Physics and Ultrasound in Medicine & Biology.

In The Last Decade

Etsuo Takada

31 papers receiving 453 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Etsuo Takada Japan 11 263 192 120 97 65 33 468
Katarzyna Dobruch‐Sobczak Poland 17 483 1.8× 274 1.4× 193 1.6× 74 0.8× 44 0.7× 64 788
Meihao Wang China 15 570 2.2× 296 1.5× 73 0.6× 36 0.4× 162 2.5× 51 868
Niall Moore United Kingdom 11 325 1.2× 57 0.3× 34 0.3× 19 0.2× 58 0.9× 20 548
Lara Harrison Finland 11 294 1.1× 75 0.4× 68 0.6× 48 0.5× 42 0.6× 14 560
Fayu Liu China 14 143 0.5× 117 0.6× 45 0.4× 15 0.2× 84 1.3× 34 671
Thomas Schlossbauer Germany 10 224 0.9× 84 0.4× 60 0.5× 23 0.2× 24 0.4× 25 347
Ioannis Pechlivanis Germany 17 126 0.5× 28 0.1× 158 1.3× 247 2.5× 66 1.0× 38 731
Masoumeh Gity Iran 14 279 1.1× 121 0.6× 63 0.5× 34 0.4× 51 0.8× 67 511
G. Lemineur France 10 119 0.5× 48 0.3× 110 0.9× 33 0.3× 11 0.2× 13 645
Mitsutaka Nemoto Japan 12 202 0.8× 118 0.6× 127 1.1× 9 0.1× 158 2.4× 50 527

Countries citing papers authored by Etsuo Takada

Since Specialization
Citations

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

Fields of papers citing papers by Etsuo Takada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Etsuo Takada. 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 Etsuo Takada. The network helps show where Etsuo Takada may publish in the future.

Co-authorship network of co-authors of Etsuo Takada

This figure shows the co-authorship network connecting the top 25 collaborators of Etsuo Takada. A scholar is included among the top collaborators of Etsuo Takada 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 Etsuo Takada. Etsuo Takada 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.
Mine, Yoshitaka, et al.. (2024). Principle of contrast-enhanced ultrasonography. Journal of Medical Ultrasonics. 51(4). 567–580. 1 indexed citations
2.
Huang, Yao‐Sian, et al.. (2017). Computer-Aided tumor diagnosis in 3-D breast elastography. Computer Methods and Programs in Biomedicine. 153. 201–209. 8 indexed citations
3.
Takada, Etsuo, et al.. (2015). Stereoscopic images of breast tumors using 3D real-time tissue elastography. Journal of Medical Ultrasonics. 42(3). 365–371. 1 indexed citations
4.
Takekawa, Hidehiro, Keisuke Suzuki, Shigeru Toyoda, et al.. (2013). Evaluation of the factors that prolong the acceleration time of the common and internal carotid arteries. 25(2). 81–85. 2 indexed citations
5.
Takekawa, Hidehiro, Keisuke Suzuki, Etsuo Takada, et al.. (2013). Acceleration time ratio for the assessment of extracranial internal carotid artery stenosis. Journal of Medical Ultrasonics. 41(1). 63–67. 9 indexed citations
6.
Miyamoto, Yukio, Toshikazu Ito, Etsuo Takada, et al.. (2012). Phase II clinical study of DD-723 (perflubutane): dose–response study in patients with breast tumors. Journal of Medical Ultrasonics. 39(2). 79–86. 10 indexed citations
7.
Chang, Ruey‐Feng, Etsuo Takada, Chiun‐Sheng Huang, et al.. (2010). Rapid image stitching and computer‐aided detection for multipass automated breast ultrasound. Medical Physics. 37(5). 2063–2073. 27 indexed citations
8.
Iwanami, Masaoki, Tomoyuki Miyamoto, Masayuki Miyamoto, Koichi Hirata, & Etsuo Takada. (2010). Relevance of substantia nigra hyperechogenicity and reduced odor identification in idiopathic REM sleep behavior disorder. Sleep Medicine. 11(4). 361–365. 54 indexed citations
9.
Moon, Woo Kyung, Chiun‐Sheng Huang, Wei-Chih Shen, et al.. (2009). Analysis of Elastographic and B-mode Features at Sonoelastography for Breast Tumor Classification. Ultrasound in Medicine & Biology. 35(11). 1794–1802. 50 indexed citations
10.
Chen, Jeon‐Hor, Chiun‐Sheng Huang, Etsuo Takada, et al.. (2009). Breast density analysis for whole breast ultrasound images. Medical Physics. 36(11). 4933–4943. 14 indexed citations
11.
Morita, Takako, Daisuke Fukuoka, Takeshi Hara, et al.. (2009). Automated analysis of breast parenchymal patterns in whole breast ultrasound images: preliminary experience. International Journal of Computer Assisted Radiology and Surgery. 4(3). 299–306. 10 indexed citations
12.
Fukuoka, Daisuke, Takeshi Hara, Hiroshi Fujita, et al.. (2007). Development of a fully automatic scheme for detection of masses in whole breast ultrasound images. Medical Physics. 34(11). 4378–4388. 75 indexed citations
13.
Takada, Etsuo, et al.. (2006). Fully automatic detection system for breast masses on ultrasound images. International Journal of Computer Assisted Radiology and Surgery. 1. 519. 3 indexed citations
14.
Chang, Ruey‐Feng, et al.. (2006). Image stitching and computer-aided diagnosis for whole breast ultrasound image. International Journal of Computer Assisted Radiology and Surgery. 1. 340–343. 7 indexed citations
15.
Tohno, Eriko, et al.. (2006). Establishment of seminars to improve the diagnostic accuracy and effectiveness of breast ultrasound. Journal of Medical Ultrasonics. 33(4). 239–244. 4 indexed citations
16.
Chang, Ruey‐Feng, Etsuo Takada, Jasjit S. Suri, et al.. (2006). Three Comparative Approaches for Breast Density Estimation in Digital and Screen Film Mammograms. PubMed. 2006. 4853–4856. 3 indexed citations
17.
Chang, Ruey‐Feng, Etsuo Takada, Jasjit S. Suri, et al.. (2006). Breast Density Analysis in 3-D Whole Breast Ultrasound Images. PubMed. 2006. 2795–2798. 10 indexed citations
18.
Sasaki, Kinro, et al.. (2002). ENDOSCOPIC ULTRASONOGRAPHY OF THE GRANULOMA IN GASTRIC ANISAKIASIS. Acta gastro-enterologica belgica. 44(6). 996–1000. 2 indexed citations
19.
Shimizu, Ken, et al.. (2001). Fine Needle Aspiration of Toxoplasmic Lymphadenitis in an Intramammary Lymph Node. Acta Cytologica. 45(2). 259–262. 3 indexed citations
20.
Takada, Etsuo, et al.. (1995). Effectiveness of Ultrasonic Examination Using a Still Image Recording System in Mass Screening for Breast Cancer. Nihon Nyugan Kenshin Gakkaishi (Journal of Japan Association of Breast Cancer Screening). 4(1). 21–29. 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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