研究業績：原著論文 (Journal papers)

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原著論文 (Journal papers)

[66] Majority or Minority: Data imbalance learning method for named entity recognition, Sota Nemoto, Shunsuke Kitada, and Hitoshi Iyatomi,  IEEE Access, 2025, (accepted). 

[65] A Practical Framework for Unsupervised Structure Preservation Medical Image Enhancement, Quan Huu Cap, Atsushi Fukuda, and Hitoshi Iyatomi, Biomedical Signal Processing and Control, Vol. 100, No.8, 106918, 2025. arXiv

[64] OpenMAP-T1: A Rapid Deep Learning Approach to Parcellate 280 Anatomical Regions to Cover the Whole Brain, Kei Nishimaki, Kengo Onda, Kunpei Ikuta, Yuto Uchida, Susumu Mori, Hitoshi Iyatomi, and Kenichi Oishi,  Human Brain Mapping,  Vol.45, No.11, e70063, 2024. Link / MedRxiv / codes 

[63] Investigation to answer three key questions concerning plant pest identification and development of a practical identification framework, Ryosuke Wayama, Yuki Sasaki, Satoshi Kagiwada, Nobusuke Iwasaki, and Hitoshi Iyatomi,  Computers and Electronics in Agriculture, Vol. 222, 109021, 2024. Link / PDF (3.04MB)

[62] Normalizing Flow to Augmented Posterior: Conditional Density Estimation with Interpretable Dimension Reduction for High Dimensional Data, Cheng Zeng, George Michailidis, Hitoshi Iyatomi and Leo L Duan, International Journal of Computer and Information Engineering, vol. 18, no. 5, pp. 306-315, 2024. Link

[61] Towards Robust Plant Disease Diagnosis with Hard-sample Re-mining Strategy, Quan Huu Cap, Atsushi Fukuda, Satoshi Kagiwada, Hiroyuki Uga, Nobusuke Iwasaki, and Hitoshi Iyatomi,  Computers and Electronics in Agriculture, Vol. 215, 108375, 2023. paper with code /  Link

[60] PCSS: Skull Stripping with Posture Correction from 3D Brain MRI for Diverse Imaging Environment, Ken Nishimaki, Kumpei Ikuta, Shingo Fujiyama, Kenichi Oishi and Hitoshi Iyatomi,  IEEE Access, vol. 11, pp. 116903-116918, 2023. Link

[59]  Image analysis in advanced skin imaging technology, Lei Bi, M Emre Celebi, Hitoshi Iyatomi, Pablo Fernandez-Penas, Jinman Kim, Computer Methods and Programs in Biomedicine, vol. 238, p.107599, 2023. (Editorial)  Link

[58] ネガティブニュースがユーザー行動に与える影響の調査,  大畑和也，飯塚洸二郎，彌冨　仁、Data-Driven Studies,  vol. 1, article 7, 2023. Link

[57]  Making Attention Mechanism More Robust and Interpretable with Virtual Adversarial Training, Shunsuke Kitada, and Hitoshi Iyatomi, Applied Intelligence, vol. 53, pp.15802-15817, 2023. Link / arXiv

[56]  DM²S²: Deep Multimodal Sequence Sets with Hierarchical Modality Attention, Shunsuke Kitada, Yuki Iwasaki, Riku Togashi, and Hitoshi Iyatomi,  IEEE Access, vol.10, pp. 120023-120034, 2022. Link

[55] 実践的な植物病自動診断のための画像生成技術,  彌冨　仁、粉体工学会誌, Vol. 59, No. 3, pp.394-399, 2022.（解説論文）Link / PDF (3.56MB)

[54]  Ad Creative Discontinuation Prediction with Multi-modal Multi-task Neural Survival Networks, Shunsuke Kitada, Hitoshi Iyatomi and Yoshifumi Seki, Applied Sciences, vol. 12, no.7, 3594, 2022.  https://doi.org/10.3390/app12073594 / Link

[53]  Disease-oriented image embedding with pseudo-scanner standardization for content-based image retrieval on 3D brain MRI, Hayato Arai, Yuto Onga, Kumpei Ikuta, Yusuke Chayama, Hitoshi Iyatomi and Kenichi Oishi,  IEEE Access, vol. 9, pp. 165326-165340, doi: 10.1109/ACCESS.2021.3129105, 2021.  Link

[52]  Attention Meets Perturbations: Robust and Interpretable Attention with Adversarial Training, Shunsuke Kitada and Hitoshi Iyatomi,  IEEE Access, vol. 9, pp. 92974-92985, 2021. Link 

[51] LASSR: Effective Super-Resolution Method for Plant Disease Diagnosis, Quan Huu Cap, Hiroki Tani, Satoshi Kagiwada, Hiroyuki Uga and Hitoshi Iyatomi,  Computers and Electronics in Agriculture, 187, 106271, 2021. arXiv/  Link

[50] LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis, Quan Huu Cap, Hiroyuki Uga, Satoshi Kagiwada and Hitoshi Iyatomi,  IEEE Trans. Automation Science and Engineering, Dec. 2020   DOI: 10.1109/TASE.2020.3041499  (in press - early access).

[49] 植物病害自動診断技術の動向と課題, 彌冨　仁、日本神経回路学会誌, Vol.26, No.4, pp.123-134, 2019.（解説論文）PDF(5.97MB)

[48] Practical plant diagnosis system for field leaf images and feature visualization, Erika Fujita, Hiroyuki Uga, Satoshi Kagiwada, and Hitoshi Iyatomi, International Journal of Engineering & Technology, vol. 7, no. 4.11, pp.49-54, 2018. PDF(441KBytes)

[47] An end-to-end practical plant disease diagnosis system for wide-angle cucumber images, Huu Quan Cap, Katsumasa Suwa, Erika Fujita, Satoshi Kagiwada, Hiroyuki Uga, and Hitoshi Iyatomi, International Journal of Engineering & Technology, vol.7, no.4.11, pp.106-111, 2018.  PDF(753KBytes)

[46] 畳み込みニューラルネットワークを使った授業映像中の聴講者の状態推定システムの構築と特徴量獲得に関する検討, 島田大樹、彌冨　仁、日本知能情報ファジィ学会誌, No.1, pp.517-526, 2017. PDF(6.1 MBytes)

[45] キュウリウイルス病の画像による診断システムの開発、宇賀博之、彌冨　仁、川崎雄介、藤田恵梨香、鍵和田　聡、植物防疫, Vol.70, No.5, pp.315-318, 2016. PDF(401KBytes)

[44] Four-class classification of skin lesions with task decomposition strategy,  Kouhei Shimizu, Hitoshi Iyatomi, M. Emre Celebi, Kerri-Ann Norton, and Masaru Tanaka, IEEE Trans. on Biomedical Engineering, Vol.62, No.1, pp.274-283, 2015. PDF(767KBytes)

[43] An ensemble classification approach for melanoma diagnosis, Gerald Schaefer, Bartosz Krawczyk, M. Emre Celebi and Hitoshi Iyatomi, Memetic computing journal, Vol.6, pp.233-240, 2014. PDF(667KBytes)

[42] Melanoma Classification based on Ensemble Classification of Dermoscopy Image Features,  Gerald Schaefer, Bartosz Krawczyk, M. Emre Celebi and Hitoshi Iyatomi and Aboul Ella Hassanien, Advanded Machine Learning and Applications Communications, Vol.488, pp.291-298, 2014. PDF(1.2MBytes)

[41] Age-related prevalence of dermatoscopic patterns of acral melanocytic nevi, Reiko Suzaki, Sumiko Ishizaki, Hitoshi Iyatomi and Masaru Tanaka, Dermatology Practical & Conceptual, Vol.4, No.1, pp.53-57, 2014. PDF(1.7MBytes)

[40] Extension of automated melanoma screening for non-melanocytic skin lesions, Kohei Shimizu, Hitoshi Iyatomi, M.Emre Celebi and Kerri-Ann Norton, International Journal of Intelligent Systems Technologies and Applications, Vol.50, No.1-2, pp.122-130,2014. PDF(299KBytes)

[39] 非侵襲自律神経疾患計測のための外乱に強い電子瞳孔計の開発, 鬼山　勝、彌冨　仁、尾川浩一、電子情報通信学会論文誌D-I, Vol.86, No.4, pp.867-875, 2013. PDF(2.2MBytes)

[38] Lesion border detection in dermoscopy images using ensembles of thresholding methods, M.Emre.Celebi, Quan Wen, Sae Hwang, Hitoshi Iyatomi and Gerald Schaefer, Skin Research and Technology, Vol.19, No.1, pp.252-258, 2013. PDF(2.2MBytes)

[37] Motion detection system accelerated by GPU for stereotactic radiosurgery, Takuya Yamakawa, Koichi Ogawa, Hitoshi Iyatomi, Etsuo Kunieda, Keisuke Usui, Naoyuki Shigematsu, Medical Imaging Technology, Vol.30, No.5, pp.268-278, 2012. 

[36] An Automated Reconstruction Algorithm for Identification of 3D Architectures of Cribriform Ductal Carcinoma in Situ, Kerri-Ann Norton, Sameera Namazi, Nicola Barnard, Mariko Fujibayashi, Gyan Bhanot, Shridar Ganesan, Hitoshi Iyatomi, Koichi Ogawa, and Troy Shinbrot,  PLoS ONE, Vol.7, No.9, e44011, Sep. 2012. PDF(756KBytes)

[35] Three-phase general border detection method for dermoscopy images using non-uniform illumination correction, Kerri-Ann Norton, Hitoshi Iyatomi, M. Emre Celebi, Mizuki Sawada, Sumiko Ishizaki, Reiko Suzaki, Ken Kobayashi, Masaru Tanaka and Koichi Ogawa, Skin Research and Technology, Vol.18, No.3, pp.290-300,  2012. PDF(390KBytes)

[34] 褥瘡重傷度と全身的予後の関係および臨床検査値と褥瘡予後の関係-1,134件の統計的検討,
石崎純子、彌冨　仁、町屋千鶴子、田中　勝,
東京女子医科大学雑誌, Vol.81, No.2, pp.96-101, 2011年4月.

[33] Automated color calibration method for dermoscopy images, Hitoshi Iyatomi, M.Emre Celebi, Gerald Schaefer, Masaru Tanaka, Computerized Medical Imaging and Graphics, Vol.35, No.2, pp.89-98, 2011. PDF(1.6MBytes)

[32] Colour and contrast enhancement for improved skin lesion segmentation, Gerald Schaefer, Maher I. Rajab, M. Emre Celebi, Hitoshi Iyatomi, Computerized Medical Imaging and Graphics, Vol35, No.2, pp.99-104, 2011.

[31] Image analysis for senile lentigo and evaluation of therapeutic effects by hydroquinone, Mizuki SAWADA, Hitoshi IYATOMI, Yoshifumi MAUMI, Ken KOBAYASHI, Reiko SUZAKI, Sumiko ISHIZAKI, Masaru TANAKA, Journal of Investigative Dermatology, Vol.140, p.60, 2010.

[30] Quantitative and objective area extraction of tinea unguium, Yasuki HATA, Hitoshi IYATOMI, Sumiko ISHIZAKI, Mizuki SAWADA, Ken KOBAYASHI, Masahiko OZEKI and Masaru TANAKA, Journal of Investigative Dermatology, Vol.140, p.59, 2010.

[29] Computerized quantification of psoriasis lesions with colour calibration: Preliminary results, Hitoshi Iyatomi, Hiroshi Oka, Masafumi Hagiwara, Ayako Miyake, Masayuki Kimoto, Koichi Ogawa and Masaru Tanaka, Clinical and Experimental Dermatology, Vol.34, No.7, pp.830-833, 2009. PDF(258KB)

[28] 劣化の少ない2値画像回転手法,  彌冨 仁、尾川浩一, 電子情報通信学会論文誌D-II, Vol.92, No.9, pp.1682-1685, 2009.

[27] An Improved Objective Evaluation Measure for Border Detection in Dermoscopy Images, M. Emre Celebi, Gerald Schaefer, Hitoshi Iyatomi, William V. Stoecker, Joseph M. Malters, and James M. Grichnik, Skin Research and Technology, Vol. 15, No.4, pp.444-450, 2009.

[26] Approximate Lesion Localization in Dermoscopy Images, M. Emre Celebi, Hitoshi Iyatomi, Gerald Schaefer, and William V. Stoecker, Skin Research and Technology, Vol. 15, No.3, pp.314-322, 2009.

[25] ダーモスコピーによる自動診断法, 田中勝、彌冨 仁,
MB Derma, Vol.149, pp.76-82, 2009.

[24] Lesion Border Detection in Dermoscopy Images, M. Emre Celebi, Hitoshi Iyatomi, Gerald Schaefer, and William V. Stoecker, Computerized Medical Imaging and Graphics, Vol.33, No.2, pp.148-153, 2009.

[23] Automatic Detection of Blue-White Veil and Related Structures in Dermoscopy Images, M. Emre Celebi, Hitoshi Iyatomi, William V Stoecker, Randy H Moss, Harold S Rabinovitz, Giuseppe Argenziano, Peter Soyer, Computerized Medical Imaging and Graphics, Vol.32, No.8, pp.670-677, 2008 Online abstract available (link to Pubmed.)

[22] Application of Support Vector Machine Classifiers to Preoperative Risk Stratification with Myocardial Perfusion Scintigraphy, Tomotaka Kasamatsu, Jun Hashimoto, Hitoshi Iyatomi,Tadaki Nakahara, Jingming Bai, Naoto Kitamura, Koichi Ogawa, Atsushi Kubo, Circulation Journal, Vol.72, No.11, pp.1829-1835, 2008. On line abstract available (link to Pubmed.)

[21] Reply to "Digital dermoscopy analysis and internet-based program for discrimination of pigmented skin lesion dermoscopic images,
M.Kimoto, M.Sakamoto, H.Iyatomi and M.Tanaka., Dermatology, Vol.217, No.4, pp.359, 2008. On line version available (link to Karger.com)

[20] An Improved Internet-based Melanoma Screening System with Dermatologist-like Tumor Area Extraction Algorithm, Hitoshi Iyatomi, Hiroshi Oka, M.Emre Celebi, Masahiro Hashimoto, Masafumi Hagiwara, Masaru Tanaka, Koichi Ogawa, Computerized Medical Imaging and Graphics, Vol.32, No.7, pp.566-579, 2008. PDF (1084KBytes)

[19] Computer-based classification of dermoscopy images of melanocytic lesions on acral volar skin Hitoshi Iyatomi, Hiroshi Oka, M Emre Celebi, Koichi Ogawa, Giuseppe Argenziano, H Peter Soyer, Hiroshi Koga, Toshiaki Saida, Kuniaki Ohara, and Masaru Tanaka, Journal of Investigative Dermatology, Vol.128, pp.2049-2054, 2008. PDF (130KBytes)

[18] 非心臓手術の心事故リスクの推定　－核医学検査の有用性の検討, 彌冨 仁、白 景明、笠松 智孝、橋本 順, 日本知能情報ファジィ学会誌 (医用システム特集号) Vol.20, No.1, pp.100-107, 2008.

[17] Three dimensional melanin distribution of acral melanocytic nevi is reflected in dermoscopy features: Analysis of parallel pattern, M.Kimoto, M.Sakamoto, H.Iyatomi and M.Tanaka. Dermatology, Vol.216, pp.205-212, 2008. Online abstract Available (link to Pubmed.)

[16] Border Detection in Dermoscopy Images Using Statistical Region Merging, M. Emre Celebi, Hassan A. Kingravi,Hitoshi Iyatomi, Y. Alp Aslandogan, William V. Stoecker, Randy H.Moss et al, Skin Research and Technology, Vol.14, Issue 3, pp.347-353, 2008.

 [15] A methodological approach to the classification of dermoscopy images, M. Emre Celebi, Hassan A. Kingravi, Bakhtiyar Uddin, Hitoshi Iyatomi, Y. Alp Aslandogan, William V. Stoecker and Randy H.Moss, Computerized Medical Imaging & Graphics, Vol.31, No.6, pp.362-373, 2007.

[12] Quantitative assessment of tumor extraction from dermoscopy images and evaluation of computer-based extraction methods for automatic melanoma diagnostic system, Hitoshi Iyatomi, Hiroshi Oka, Masataka Saito, Ayako Miyake, Masayuki Kimoto, Jun Yamagami, Seiichiro Kobayashi, Akiko Tanikawa, Masarumi Hagiwara, Giuseppe Argenziano, H.Peter Soyer and Masaru Tanaka. Melanoma Research, Vol.16, No.2, pp.183-190, 2006 PDF (259KBytes)

[11] Reply to "Digital dermoscopy analysis and internet-based program for discrimination of pigmented skin lesion dermoscopic images, Oka H, Iyatomi H, Hashimoto M and Tanaka M, British Journal of Dermatology, Vol.154, No.3, pp.570-571, 2006 Online abstract Available (link to Pubmed.)

[10] 悪性黒色腫とクラーク母斑のダーモスコピー画像におけるDotsのコンピュータを用いた検出と評価, 吉野寿美、岡博史、田中勝、彌富仁、橋本正弘、本山比佐夫, Skin cancer, Vol.20, No.2, pp.183-189, 2005.

[9] 悪性黒色腫のダーモスコピー画像における特有色のコンピュータ解析による検出, 本山比佐夫、岡博史、田中勝、彌富仁、橋本正弘、吉野寿美, Skin cancer, Vol.20, No.2, pp.190-196, 2005.

[8] 掌足庶の病変を含むメラノーマとクラーク母斑のニューラルネットワークを用いた自動判別サーバ, 橋本正弘、岡博史、田中勝、彌富仁、本山比佐夫、吉野寿美, Skin cancer, Vol.20, No.2, pp.197-202, 2005.

[7] 追加学習可能なファジィ推論ニューラルネットワークの提案と画像認識への応用,
居谷 道明、彌富 仁、萩原将文,
日本知能情報ファジィ学会論文誌 Vol.17, No.1, pp.60-67, 2005.

[6] Adaptive Fuzzy Inference Neural Network, Hitoshi Iyatomi and Masafumi Hagiwara, Pattern Recognition, Vol 37, issue 10, pp.2049-2057, 2004. abstract (link to Elsevier science)/PDF (166KBytes)

[5] 悪性黒色腫自動診断システムのためのダーモスコピー像からの腫瘍領域抽出法, 彌冨　仁、岡　博史、橋本　正弘、田中　勝、萩原　将文、尾川 浩一, Medical Imaging Technology, Vol.22, No.4, pp.197-200, 2004. PDF (406KB)

[4] Internet-based program for automatic discrimination of dermoscopic images between melanomas and Clark nevi, Oka H, Hashimoto M, Iyatomi H, Argenziano G, Soyer HP and Tanaka M, British Journal of Dermatology No.150, issue 5, p.1041, 2004. abstract (link to PubMed)

[3] 適応ファジィニューラルネットワークとアクティブ探索法を用いた画像認識, 彌冨  仁、萩原将文 電子情報通信学会論文誌 D-II,Vol.J87-D2, No.4, pp.958-966, 2004. PDF (742KBytes)

[2] Scenery Image Recognition and Interpretation using Fuzzy Inference Neural Networks, Hitoshi Iyatomi and Masafumi Hagiwara, Pattern Recognition Vol.35, issue 8, pp.1793-1806, 2002. PDF (522KBytes)

[1] ファジィ推論ニューラルネットワークを用いた風景画像からの知識抽出と認識, 彌冨　 仁、萩原将文 電子情報通信学会論文誌 D-II Vol.J82-D-II No.4 pp.685-693, 1999. PDF (In Japanese: 269KB)