Takeshi Hara
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- Radiomics and Machine Learning in Medical Imaging 56
- Retinal Imaging and Analysis 31
- Oral Surgery top 1%
- Dental Radiography and Imaging 24
- Biological Psychiatry top 2%
- Ophthalmology top 0.5%
- Glaucoma and retinal disorders 25
- Health Informatics top 2%
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- Medical Image Segmentation Techniques 61
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- AI in cancer detection 61
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- Medical Imaging and Analysis 34
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- Lymphoma Diagnosis and Treatment 27
- Co-authors
- Hiroshi FujitaChisako MuramatsuXiangrong ZhouHisashi TsurumiHisataka MoriwakiYuji HatanakaYongbum LeeTakeo Ishigaki
- Partner nations
- JapanUnited StatesChina
In The Last Decade
Takeshi Hara
312 papers receiving 5.3k citations
Hit Papers
Peers
Comparison fields: 5 of 169
- Radiology, Nuclear Medicine and Imaging 2.2k
- Oral Surgery 632
- Biological Psychiatry 199
- Ophthalmology 700
- Health Informatics 81
Countries citing papers authored by Takeshi Hara
This map shows the geographic impact of Takeshi Hara'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 Takeshi Hara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takeshi Hara more than expected).
Fields of papers citing papers by Takeshi Hara
This network shows the impact of papers produced by Takeshi Hara. 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 Takeshi Hara. The network helps show where Takeshi Hara may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Takeshi Hara, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 9 | |
| 2 | 2022 | 18 | |
| 3 | 2020 | 2 | |
| 4 | 2020 | 9 | |
| 5 | 2019 | 8 | |
| 6 | 2017 | 3 | |
| 7 | 2009 | 96 | |
| 8 | Automated Shape Analysis of Optic Disc on Retinal Fundus Images | 2009 | 0 |
| 9 | An artery-vein classification using top-hat image and detection of arteriolar narrowing on retinal images | 2007 | 2 |
| 10 | 2006 | 0 | |
| 11 | 2004 | 1 | |
| 12 | Automatic Segmentation of Hepatic Tissue and 3D Volume Analysis of Cirrhosis in Multi-Detector Row CT Scans and MR Imaging | 2004 | 13 |
| 13 | 2002 | 5 | |
| 14 | 2002 | 6 | |
| 15 | 2001 | 0 | |
| 16 | 2000 | 1 | |
| 17 | 2000 | 3 | |
| 18 | 2000 | 1 | |
| 19 | 2000 | 1 | |
| 20 | Detection of Microcalcifications on Mammograms Using Artificial Neural Networks | 1997 | 2 |
About Takeshi Hara
Takeshi Hara is a scholar working on Biological Psychiatry, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 327 papers that have together received 5.5k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (61 papers), AI in cancer detection (61 papers), Radiomics and Machine Learning in Medical Imaging (56 papers), Medical Imaging and Analysis (34 papers), Retinal Imaging and Analysis (31 papers), Lymphoma Diagnosis and Treatment (27 papers), Glaucoma and retinal disorders (25 papers) and Dental Radiography and Imaging (24 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (2.2k citations), Oral Surgery (632 citations) and Biological Psychiatry (199 citations). Takeshi Hara has collaborated with scholars based in Japan, United States and China. Frequent co-authors include Hiroshi Fujita, Chisako Muramatsu, Xiangrong Zhou, Hisashi Tsurumi, Hisataka Moriwaki, Yuji Hatanaka, Yongbum Lee, Takeo Ishigaki, Tatsuro Hayashi and Shigeki Itoh. Their work appears in journals such as Blood, PLoS ONE and Scientific Reports.
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.