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Hidetaka Arimura Laboratory, Kyushu University@

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Hidetaka Arimura Laboratory

Kyushu University, Division of Medical Quantum Sciences
Department of Health Sciences, Faculty of Medical Sciences

"Artificial intelligence-based diagnostic and treatment systems"

Our Keywords : Precision Medicine, Medical AI, Radiomics, Medical Images,
Data Science, Medical Physics, Medical Image Analysis, Medical Image Processing
Pattern Recognition, Machine Learning, Radiation Physics

Publication




Recurrence prediction with local binary pattern-based dosiomics in patients with head and neck squamous cell carcinoma

Hidemi Kamezawa, Hidetaka Arimura.et al.
Physical and Engineering Sciences in Medicine (accepted on Nov.21,2022)


Dual segmentation models for poorly and well-differentiated hepatocellular carcinoma using two-step transfer deep learning on dynamic contrast-enhanced CT images

Noriyuki Nagami, Hidetaka Arimura, Junichi Nojiri, Cui Yunhao, Kenta Ninomiya,Manabu Ogata, Mitsutoshi Oishi, Keiichi Ohira, Shigetoshi Kitamura, Hiroyuki Irie
Physical and Engineering Sciences in Medicine (accepted on Nov.17,2022)


Prediction of intracranial aneurysm rupture risk using non-invasive radiomics analysis based on follow-up magnetic resonance angiography images:A preliminary study

Masayuki Yamanouchi, Hidetaka Arimura, Takumi Kodama, Akimasa Urakami
Applied Sciences, 2022, 12(17), 8615
August 28, 2022
https://www.mdpi.com/2076-3417/12/17/8615

Relapse predictability of topological signature on pretreatment planning CT images of stage I non-small cell lung cancer patients before treatment with stereotactic ablative radiotherapy

Kodama Takumi, Arimura Hidetaka, Shirakawa Yumi, Ninomiya Kenta, Yoshitake Tadamasa, Shioyama Yoshiyuki.
Thoracic Cancer, 16 June 2022
https://doi.org/10.1111/1759-7714.14483



Synergistic combination of a topologically invariant imaging signature and a biomarker for the accurate prediction of symptomatic radiation pneumonitis before stereotactic ablative radiotherapy for lung cancer: A retrospective analysis

Kenta Ninomiya, Hidetaka Arimura, Tadamasa Yoshitake, Taka-aki Hirose, Yoshiyuki Shioyama, PLOS ONE, January 31, 2022
https://doi.org/10.1371/journal.pone.0263292



Feasibility for prediction of primary cancer sites of brain metastases based on Hessian index images

Kazutoshi MORIYAMA, Hidetaka ARIMURA, Kazuma KOBAYASHI, Quoc CUONG-LE, Akimasa URAKAMI, Kenta NINOMIYA, Takumi KODAMA, Hiroyuki OKAMOTO, Hiroshi IGAKI
Medical Imaging and Information Sciences
2022,39(3);57-67, September 30, 2022
(English abstract, Japanese body text)
https://doi.org/10.11318/mii.39.57


News & Informationnews

December/24/2022
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Decembe/11/2022
Prof. Arimura has been invited to have a talk in AOCMP 2022, Taiwan
Decembe/09/2022
Prof. Arimura has been invited to have a talk in MCOR 2022, Malaysia
November/21/2022
A paper on "Recurrence prediction with local binary pattern-based dosiomics in patients with head and neck squamous cell carcinoma" has been accepted in Physical and Engineering Sciences in Medicine
Kamezawa H, Arimura H.et al.
November/17/2022
A paper on "Dual segmentation models for poorly and well-differentiated hepatocellular carcinoma using two-step transfer deep learning on dynamic contrast-enhanced CT images" has been accepted in Physical and Engineering Sciences in Medicine
Nagami N, Arimura H, et al.
November/10/2022
Prof. Arimura received a Highly Cited Award in 35th JASTRO at Hiroshima
October/25/2022
Welcome BBQ party at Ohohori park
October/01/2022
New members have joined our laboratory! Please See Member
September/28/2022
Mr. Kodama received Research Fellowships for Young Scientists! JSPS
September/22/2022
Graduation Ceremony for international students at Kyushu University Congratulations! Cui-kun
September/20/2022
Symposium on Intelligent Data Science for Radiological Imaging (iDSRI) between Universiti Malaya & Kyushu University, Participants:79.
September/17/2022
One poster presentation at 114th JSMP in Nagasaki (Cui Y.)
September/13/ 2022
Arimura had a Keynote Speech in 5th International Conference of Computer and Informatics Engineering (IC2IE) Virtually Conference, Indonesia
August/28/2022
New paper published gPrediction of Intracranial Aneurysm Rupture Risk Using Non-Invasive Radiomics Analysis Based on Follow-Up Magnetic Resonance Angiography Images: A Preliminary Studyh
Yamanouchi M, Arimura H, et al.
Applied Sciences, 2022, 12(17), 8615
https://www.mdpi.com/2076-3417/12/17/8615
July/30/2022
New paper published "Feasibility for prediction of primary cancer sites of brain metastases based on Hessian index images"
MORIYAMA K, ARIMURA H, et al.
Medical Imaging and Information Sciences
2022,39(3);57-67, September 30, 2022
(English abstract, Japanese body text) 57-67 https://doi.org/10.11318/mii.39.57
July/29-31/2022
Three Oral presentations at JAMIT2022 in Nagoya (Uchino K, Hirakawa Y, Kodama T)
July/10-14/2022
One ePoster presentation at AAPM2022, LIVE and IN-PERSON Meeting (Iwasaki T.)
June/16/2022
New paper published " Relapse predictability of topological signature on pretreatment planning CT images of stage I non-small cell lung cancer patients before treatment with stereotactic ablative radiotherapy"
Kodama T, Arimura H, et al. Thoracic Cancer 2022
https://doi.org/10.1371/journal.pone.0263292
June/12/2022
Two Oral presentations Medical Physics and Biomedical Engineering (IUPESM WC2022) in Singapore hybrid congress (Cui Y, Kodama T.)
April/14-17/2022
Four Oral presentations at JRC2022 in Yokohama (Ikushima K, Iwasaki T, Furuta R, Jin Y)
Invited Talk at JSMP on April 17 (Arimura H)
April/01/2022
New members have joined our laboratory! Please See Member
March/23/2022
Graduation Ceremony at Kyushu University
March/16/2022
Symposium on Intelligent Data Science for Radiological Imaging (iDSRI) between Universiti Malaya & Kyushu University
January/ 31/ 2022
New paper published " Synergistic combination of a topologically invariant imaging signature and a biomarker for the accurate prediction of symptomatic radiation pneumonitis before stereotactic ablative radiotherapy for lung cancer: A retrospective analysis"
Ninomiya K, Arimura H, et al. PLOS ONE
https://doi.org/10.1371/journal.pone.0263292

Hide Arimura Lab

Hidetaka Arimura, PhD
Division of Medical Quantum Science, Department of Health Sciences, Faculty of Medical Sciences,
Kyushu University
3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan