研究業績：国際会議proceedings
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国際会議proceedings
[97] DDD: Discriminative difficulty distance for plant disease diagnosis, Yuji Arima, Satoshi Kagiwada, and Hitoshi Iyatomi, Proc. AAAI conference 2025 (workshop), Feb. 2025 (accepted)
[96] Few-shot metric domain adaptation: practical learning strategies for an automated plant disease diagnosis, Shoma Kudo, Satoshi Kagiwada, and Hitoshi Iyatomi, Proc. AAAI conference 2025 (workshop), Feb. 2025 (accepted)
[95] iCBIR-Sli: Interpretable content-based image retrieval with 2D slice embeddings, Shuhei Tomoshige, Hatao Muraki, Kenichi Oishi, and Hitoshi Iyatomi, Proc. SPIE Medical Imaging Conference 2025, Feb. 2025 (accepted)
[94] Domain-invariant feature learning in brain MR imaging for content-based image retrieval, Shuya Tobari, Shuhei Tomoshige, Hatao Muraki, Kenichi Oishi, and Hitoshi Iyatomi, Proc. SPIE Medical Imaging Conference 2025, Feb. 2025 (accepted)
[93] ReViSE : Proposal of Framework which Enables Seamless and Flexible Integration of Real and Virtual Objects for Video See-Through MR, Kouki Suzuki, Eito Yanagisawa, Hitoshi Iyatomi, and Sousuke Nakamura, Proc. IEEE/SICE International Symposium on System Integration (SII) 2025, Jan. 2025 (accepted)
[92] Extended Japanese Commonsense Morality Dataset with Masked Token and Label Enhancement, Ohashi Takumi, Tsubasa Nakagawa, and Hitoshi Iyatomi, Proc. 33rd ACM International Conference on Information & Knowledge Management (CIKM2024), pp. 3964-3968, Oct. 2024. Link
[91] Hierarchical Object Detection and Recognition Framework for Practical Plant Disease Diagnosis, Kohei Iwano, Shogo Shibuya, Satoshi Kagiwada, Hitoshi Iyatomi, Proc. IEEE International Conference on Agrosystem Engineering, Technology & Applications (IEEE AGRETA2024), Sep. 2024. (accepted) arXiv preprint
[90] Majority or Minority: Data imbalance learning method for named entity recognition, Sota Nemoto, Shunsuke Kitada, and Hitoshi Iyatomi, Proc. International Conference on Learning Representations (PMLR4RS - ICLR2024 workshop), May. 2024. Link
[89] Isometric feature embedding for content-based image retrieval , Hayato Muraki, Kei Nishimaki, Shuya Tobaru, Kenichi Oishi, and Hitoshi Iyatomi, Proc. Information Sciences and Systems (CISS2024), Mar. 2024. PDF (443KB)
[88] Acquiring a low-dimensional, environment-independent representation of brain MR images for content-based image retrieval, Shuya Tobari, Kenichi Oishi, Hitoshi Iyatomi, Proc. IEEE System, Man, and Cybernetics (IEEE SMC2023), pp. 5096-5101, Oct. 2023. PDF(649KB)
[87] How are negative articles consumed? A quantitative analysis of user behavior in a real news service?, Kazuya Ohata, Hitoshi Iyatomi, Hajime Morita, Kojiro Iizuka, Proc. IEEE System, Man, and Cybernetics (IEEE SMC2023), pp. 5311-5316, Oct. 2023.PDF(685KB)
[86] Feedback is needed for retakes: An explainable poor image notification framework, Kazuya Ohata, Shunsuke Kitatda, and Hitoshi Iyatomi, Proc. IEEE International Conference on Smart Communities: Improving Quality of Life Using ICT. IoT and AI (IEEE HONET2022), pp.166-171, Dec. 2022 Link
[85] Expressions Causing Differences in Emotion Recognition in Social Networking Service Documents , Tsubasa Nakagawa, Shunsuke Kitada, and Hitoshi Iyatomi, Proc. 31st ACM International Conference on Information & Knowledge Management (CIKM2022), pp.4349-4353, Oct. 2022. Link
[84] Loc-VAE: Learning Structurally Localized Representation from 3D Brain MR Images for Content-Based Image Retrieval, Kei Nishimaki, Kumpei Ikuta, Yuto Onga, Hitoshi Iyatomi, and Kenichi Oishi, Proc. IEEE System, Man, and Cybernetics (IEEE SMC2022), pp. 2433-2438, Oct. 2022. Link
[83] Key area acquisition training for practical image-based plant disease diagnosis, Kaito Odagiri, Shogo Shibuya, Quan Huu Cap, and Hitoshi Iyatomi, Proc. IEEE Signal Processing and its Applications (IEEE CSPA 2022), pp.277-282, May. 2022. PDF(12.5MB), Link
[82] Super-resolution for Brain MR Images from a Significantly Small Amount of Training Data, Kumpei Ikuta, Hitoshi Iyatomi, and Kenichi Oishi, Proc. AAAI conference on artificial intelligence, Feb. 2022. Link
[81] Validation of Prerequisites for Correct Performance Evaluation of Image-based Plant Disease Diagnosis using Reliable 221K Images Collected from Actual Fields, Shogo Shibuya, Quan Huu Cap, Shunta Nagasawa, Satoshi Kagiwada, Hiroyuki Uga, and Hitoshi Iyatomi, Proc. AAAI conference on artificial intelligence, (accepted) Feb. 2022. Link
[80] Validity-Based Sampling and Smoothing Method for Multiple Reference Image Captioning, Shunta Nagasawa, Yotaro Watanabe and Hitoshi Iyatomi, 2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL2021), pp.36-41, Jun. 2021.Link
[79] Bulk Production Augmentation Towards Explainable Melanoma Diagnosis, Kasumi Obi, Quan Huu Cap, Noriko Umegaki-Arao, Masaru Tanaka, and Hitoshi Iyatomi, Proc. IEEE EMBC Conferences on Biomedical Engineering and Science (IEEE IECBES2020), pp.454-459, Mar. 2021. Student Best Paper Award arXiv PDF(2.26MB)
[78] PPIG: Productive and Pathogenic Image Generation for Plant Disease Diagnosis, Satoi Kanno, Shunta Nagasawa, Quan Huu Cap, Hiroyuki Uga, Satoshi Kagiwada, and Hitoshi Iyatomi, Proc. IEEE EMBC Conferences on Biomedical Engineering and Science (IEEE IECBES2020), pp.554-559, Mar. 2021. PDF (3.24MB)
[77] MIINet: An Image Quality Improvement Framework for Supporting Medical Diagnosis, Quan Huu Cap, Hitoshi Iyatomi and Atsushi Fukuda, International Workshop on Artificial Intelligence for Healthcare Applications (ICPR Workshop 2020), Jan. 2021 Link, arXiv
[76] Text Classification through Glyph-aware Disentangled Character Embedding and Semantic Sub-character Augmentation, Takumi Aoki, Shunsuke Kitada, and Hitoshi Iyatomi, Proc. Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Languate Processing (AACL-IJCNLP2020): student research workshop, Dec. 2020. Link arXiv preprint arXiv:2011.04184
[75] AraDIC: Arabic Document Classification Using Image-Based Character Embeddings and Class-Balanced Loss, Mahmoud Daif, Shunsuke Kitada, and Hitoshi Iyatomi, Proc. 2020 Annual Conference of the Association for Computational Linguistics (ACL2020): student research workshop, pp.214-221, Jul. 2020. PDF (363KB)
[A3] LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis, Quan Huu Cap, Hiroyuki Uga, Satoshi Kagiwada and Hitoshi Iyatomi, Feb. 2020, arXiv preprint arXiv:2002.10100
[74] Efficient feature embedding of 3D brain MRI images for content-based image retrieval with deep metric learning, Yuto Onga, Shingo Fujiyama, Hayato Arai, Yusuke Chayama, Hitoshi Iyatomi, and Kenichi Oishi, Proc. IEEE BigData2019, (Advances in High Dimensional Big Data (AdHD)) , pp.3764-3769, Dec. 2019. PDF(772KB)
[73] Towards Explainable Melanoma Diagnosis: Prediction of Clinical Indicators using Semi-supervised and Multi-task Learning, Seiya Murabayashi and Hitoshi Iyatomi, Proc. IEEE BigData2019, (6th International Workshop on Big Data Analytic Technology for Bioinformatics and Health Informatics (KDDBHI 2019)) , pp. 4853-4857, Dec. 2019. PDF(519KB)
[72] Stochastic Gastric Image Augmentation for Cancer Detection from X-ray Images, Hideaki Okamoto, Quan Huu Cap, Takakiyo Nomura, Hitoshi Iyatomi, and Jun Hashimoto, Proc. IEEE BigData2019, (6th International Workshop on Big Data Analytic Technology for Bioinformatics and Health Informatics (KDDBHI 2019)) , pp. 4858-4663, Dec. 2019. PDF(1.71MB)
[71] AOP: An Anti-overfitting Pretreatment for Practical Image-based Plant Diagnosis, Takumi Saikawa, Quan Huu Cap, Satoshi Kagiwada, Hiroyuki Uga, and Hitoshi Iyatomi, Proc. IEEE BigData2019, (Big Food and Nutrition Data Management and Analysis (BFNDMA 2019)), pp. 5177-5182, Dec. 2019. PDF(2.84MB)
[70] A comparable study: Intrinsic difficulties of practical plant diagnosis from wide-angle images, Katsumasa Suwa, Quan Huu Cap, Ryunosuke Kotani, Hiroyuki Uga, Satoshi Kagiwada, and Hitoshi Iyatomi, Proc. IEEE BigData2019, (Big Food and Nutrition Data Management and Analysis (BFNDMA 2019)), pp. 5195-5201, Dec. 2019. PDF(7.61MB)
[69] Conversion Prediction using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creatives, Shunsuke Kitada, Hitoshi Iyatomi, and Yoshifumi Seki, Proc. 25th ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD2019), Aug. 2019. PDF (1.32MB)
[68] Super-resolution for practical automated plant disease diagnosis system , Huu Quan Cap, Hiroki Tani, Hiroyuki Uga, Satoshi Kagiwada, and Hitoshi Iyatomi, Proc. Information Sciences and Systems (CISS2019), Mar. 2019. PDF (562KB)
[67] End-to-End Text Classification via Image-based Embedding using Character-level Networks, Shunsuke Kitada, Ryunosuke Kotani and Hitoshi Iyatomi, Proc. IEEE Applied Imagery Pattern Recognition (IEEE AIPR 2018), Oct. 2018. PDF (1.59MB)
[66] Diagnosis of Multiple Infections of Cucumber with Convolutional Neural Networks, Hiroki Tani, Satoshi Kagiwada, Hiroyuki Uga and Hitoshi Iyatomi, Proc. IEEE Applied Imagery Pattern Recognition (IEEE AIPR 2018), Oct. 2018. PDF(3.43MB)
[65] Practical plant diagnosis system for field leaf images and feature visualization, Erika Fujita, Hiroyuki Uga, Satoshi Kagiwada, and Hitoshi Iyatomi, Proc. International Symposium on Computational Intelligence and Application (ISCIA2018), Jul. 2018.
[64] 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, Proc. International Symposium on Computational Intelligence and Application (ISCIA2018), Jul. 2018. Best Paper Award
[63] Significant Dimension Reduction of 3D Brain MRI using 3D Convolutional Autoencoders, Hayato Arai, Yusuke Chayama, Hitoshi Iyatomi, and Kenichi Oishi, Proc IEEE Biomedical Engineering (IEEE EMBC 2018), pp.5162-5165, Jul.2018. PDF(1.49MB)
[62] One-dimensional Convolutional Neural Network for Android Malware Detection, Chihiro Hasegawa and Hitoshi Iyatomi, Proc. IEEE Signal Processing and its Applications (IEEE CSPA 2018), pp.101-104, Mar. 2018. PDF(97KB)
[61] Web Application Firewall using Character-level Convolutional Neural Network, Michiaki Ito and Hitoshi Iyatomi, Proc. IEEE Signal Processing and its Applications (IEEE CSPA 2018), pp.105-108, Mar. 2018. PDF (130KB) Best Paper Award
[60] A Deep Learning Approach for on-site Plant Leaf Detection, Quan Huu Cap, Erika Fujita, Satoshi Kagiwada, Hiroyuki Uga, and Hitoshi Iyatomi, Proc. IEEE Signal Processing and its Applications (IEEE CSPA 2018), pp.120-123, Mar. 2018. PDF(549KB)
[59] Basic Investigation on a Robust and Practical Plant Diagnostic System, Erika Fujita, Yusuke Kawasaki, Hiroyuki Uga, Satoshi Kagiwada and Hitoshi Iyatomi, Proc. IEEE Machine Learning and its Applications (IEEE ICMLA 2016), pp.989-992, Dec. 2016. PDF(196KB)
[58] Document Classification through Image-Based Character Embedding and Wildcard Training, Daiki Shimada, Ryunosuke Kotani and Hitoshi Iyatomi, Proc. IEEE BigData 2016 ( Big Data and Natural Processing Workshop (BigNLP 2016), pp.3922-3927, Dec. 2016. PDF(600KB)
[57] Simple and Effective Pre-processing for Automated Melanoma Discrimination based on cytological findings, Takuya Yoshida, M.Emre Celebi, Gerald Scahefer and Hitoshi Iyatomi, Proc. IEEE BigData 2016 (3rd Big Data Analytic Technology for Bioinformatics and Health Informatics (KDDBHI), pp.3439-3442, Dec. 2016. PDF(255KB)
[56] Protptype of super-resolution camera-array system, Daiki Hirao and Hitoshi Iyatomi, Lectures Notes in Computer Science, Vol. 9474, Vol. 1, pp.911-920, Dec. 2015. (International Symposium on Visual Computing 2015 (ISVC2015)), Dec. 2015. PDF(382KB)
[55] Automated habit detection system: A feasibility study, Hiroki Misawa, Takashi Obara and Hitoshi Iyatomi, Lectures Notes in Computer Science, Vol. 9475, Vol. 2, pp.16-23, Dec. 2015. (International Symposium on Visual Computing 2015 (ISVC2015)), Dec. 2015. PDF(734KB)
[54] Building of the readable decision trees for automated melanoma discrimination, Keiichi Ohki, M.Emre Celebi, Gerald Schaefer and Hitoshi Iyatomi, Lectures Notes in Computer Science, Vol. 9475, Vol. 2, pp.712-721, Dec. 2015. (International Symposium on Visual Computing 2015 (ISVC2015)), Dec 2015. PDF(898KB)
[53] Basic Study of Automated Diagnosis of Viral Plant Diseases with Convolutional Neural Networks, Yusuke Kawasaki, Hiroyuki Uga, Satoshi Kagiwada, and Hitoshi Iyatomi, Lectures Notes in Computer Science, Vol. 9475, Vol. 2, pp.638-645, Dec. 2015. (International Symposium on Visual Computing 2015 (ISVC2015)), Dec. 2015. PDF(8.9MB)
[52] Automated image registration and color calibration of dermoscopy images during the clinical follow-up, Hitoshi Iyatomi, Daiji Furusho, Itaru Dekio and Masaru Tanaka, Proc. 4th World Congress of Dermoscopy and Skin Imaging, Apr. 2015. PDF (2.01MB)
[51] Dermoscopic follow-up of 16 cases of regressing Spitz nevi, Itaru Dekio, Hitoshi Iyatomi, Mizuki Sawada, Sumiko Ishizaki and Masaru Tanaka, Proc. 4th World Congress of Dermoscopy and Skin Imaging, Apr. 2015.
[50] Feasibility study on evaluation of audience’s concentration in the classroom with deep convolutional neural networks, Ryosuke Yoshihashi, Daiki Shimada, Hitoshi Iyatomi, Proc. IEEE Teaching, Assessment and Learning for Engineering (IEEE TALE 2014), Dec. 2014. PDF(461KB)
[49] Accurate discrimination of Alzheimer's disease from other dementia and/or normal sujects using SPECT specific volume analysis, Hitoshi Iyatomi, Jun Hashimoto, Fumihito Yoshii, Toshiki Kazama, Shuichi Kawada and Yutaka Imai, Proc. SPIE Medical Imaging Conference 2014, Vol.9035, doi:10.1117/12.2044011, Feb. 2014. PDF(107KB)
[48] A preliminary study for fully automated quantification of paoriasis severity using image mapping, Kazuhiro Mukai and Hitoshi Iyatomi, Proc. SPIE Medical Imaging Conference 2014, Vol.9035, doi: 10.1117/12.2043446, Feb. 2014. PDF(418KB)
[47] Preliminary experiments on quantification of skin condition, Kenzo Kitajima and Hitoshi Iyatomi, Proc. SPIE Medical Imaging Conference 2014, Vol.9037, doi: 10.1117/12.2044018, Feb. 2014. PDF(271KB)
[46] Registration and color calibration for dermoscopy images in time-course analysis, Daiji Furusho and Hitoshi Iyatomi, Proc. SPIE Medical Imaging Conference 2014, Vol.9035, doi: 10.1117/12.2044019, Feb. 2014. PDF(441KB)
[45] Melanoma classification using dermoscopy imaging and ensemble learning, Gerald Schaefer, Bartosz Krawczyk, M. Emre Celebi and Hitoshi Iyatomi, Proc. 2nd IAPR Asian Conference on Pattern Recognition (ACPR2013), pp.386-390, Nov. 2013.
[44] Production of the grounds for melanoma classification using adaptive fuzzy inference neural network, Yuji Ikuma and Hitoshi Iyatomi, Proc IEEE System, Man and Cybernetics (SMC2013), pp.2570-2575, Oct. 2013. PDF(1.0MB)
[43] 3D Architecture of Ductal Carcinoma in Situ From Image Reconstructions, Kerri-Ann Norton, Sameera Namazi, Nicola Barnard, Mariko Fujibayashi, Gyan Bhanot, Shridar Ganesan, Hitoshi Iyatomi, Koichi Ogawa, and Troy Shinbrot, Proc. IEEE EMBS Conference on Biomedical Engineering (IECBES 2012), pp.631-635, Dec.2012. PDF(56KB)
[42] Development of Robust Video-oculography System for Non-invasive Autonomic Nerve Quantification Masaru Kiyama, Hitoshi Iyatomi and Koichi Ogawa, Proc. IEEE EMBS Conference on Biomedical Engineering (IECBES 2012), pp.853-856, Dec.2012. PDF(1.12MB)
[41] Extension of automated melanoma screening for non-melanocytic skin lesions Kohei Shimizu, M.Emre Celebi, Kerri-Ann Norton and Hitoshi Iyatomi, Proc. 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP12), pp.16-19, Nov. 2012.
[40] Robust Video-oculography for Non-invasive Autonomic Nerve Quantification Masaru Kiyama, Hitoshi Iyatomi, Koichi Ogawa Proc. IEEE International Conference of the Engineering in Medicine and Bilology Society (EMBS 2011), pp.494-497, 2011.PDF(516KB)
[39] Feasibility Evaluation of a Motion Detection System with Face Images for Stereotactic Radiosurgery Takuya Yamakawa, Koichi Ogawa, Hitoshi Iyatomi, Etsuo Kunieda Proc. IEEE International Conference of the Engineering in Medicine and Bilology Society (EMBS 2011), pp.425-428, 2011.
[38] Automated color normalization for dermoscopy Images Hitoshi Iyatomi, M. Emre Celebi, Gerald Schaefer, Masaru Tanaka Proc. IEEE International Conference on Image Processing (ICIP 2010), Hong Kong, China, pp.4357-4360, Sep. 2010.
[37] Robust border detection in dermosciopy images using threshold fusion, M. Emre Celebi, Sae Hwang, Hitoshi Iyatomi, Gerald Schaefer Proc. IEEE International Conference on Image Processing (ICIP 2010), Hong Kong, China, pp.2541-2544, Sep. 2010.
[36] 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.S140, p.59, Sep. 2010.
[35] 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.S140, p.60, Sep. 2010.
[34] Skin lesion segmentation using an improved snake model, Huiyu Zhou, Gerald Schaefer, M. Emre Celebi, Hitoshi Iyatomi, Tangwei Liu, Faquan Lin Proc. IEEE International Conference of the Engineering in Medicine and Bilology Society (EMBS 2010), Buenos Aires, Argentina, pp.1974-1977, Aug, 2010.
[33] Classification of melanocytic skin lesions from non-melanocytic lesions, Hitoshi Iyatomi, Kerri-Ann Norton, M. Emre Celebi, Gerald Schaefer, Masaru Tanaka, and Koichi Ogawa Proc. IEEE International Conference of the Engineering in Medicine and Bilology Society (EMBS 2010), Buenos Aires, Argentina, pp.5407-5410, Aug, 2010.
[32] Detection Method for Melanocytic and Non-Melanocytic Dermoscopy Images, Kerri-Ann Norton, Hitoshi Iyatomi, M. Emre Celebi, Gerald Schaefer, Masaru Tanaka, and Koichi Ogawa Proc. IEEE International Conference of the Engineering in Medicine and Bilology Society (EMBS 2010), Buenos Aires, Argentina, pp.5403-5406, Aug, 2010.
[31] Perioperative risk prediction Hitoshi Iyatomi, Tomotaka Kasamatsu, Jun Hashimoto, M.Emre Celebi, Gerald Schaefer and Koichi Ogawa Proc. IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB 2009), Larnaca, Cyprus, pp.1-4, Nov. 2009. PDF(108KB)
[30] Skin lesion segmentation using cooperative neural network edge detection and colour normalisation, Gerald Schaefer, Maher Rajab, M. Emre Celebi and Hitoshi Iyatomi Proc. IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB 2009), Larnaca, Cyprus, pp.1-4, Nov. 2009.
[29] Skin Lesion Extraction in Dermoscopic Images Based on Colour Enhancement and Iterative Segmentation Gerald Schaefer, M. Rajab, M.Emre Celebi, and Hitoshi Iyatomi Proc. IEEE International Conference on Image Processing (ICIP 2009), Cairo, Egypt, pp.3361-3364, Nov. 2009.
[28] Contrast enhancement in dermoscopy images by maximizing a histogram bimodality measure M. Emre Celebi, Hitoshi Iyatomi, Gerald Schaefer Proc. IEEE International Conference on Image Processing (ICIP 2009), Cairo, Egypt, pp.2601-2604, Nov. 2009.
[27]Motion detection system with three USB cameras and an active search algorithm for stereotactic radiosurgery Go Mamiya, Etsuo Kunieda, Yohei Oku, Hitoshi Iyatomi, Koichi Ogawa Proc.11th World Congress on Medical Physics and Biomedical Engineering, Germany, pp.37-40, Sep.2009.
[26] Localization of lesions in dermoscopy images using ensembles of thresholding methods. M.E.Celebi, Hitoshi Iyatomi, Gerald Scheafer, William V.Stoecker, Lectures Note in Computer Science, Vol.5414, pp.1094-1103, Jan.2009.
[25] An analysis of 575 cases of pressure ulcer in a university hospital: correlation between the prognosis of the patients and the severity of their pressure ulcer Sumiko Ishizaki, Hitoshi Iyatomi, Chizuko Machiya, Masaru Tanaka Proceedings of 10th China-Japan joint meeting of Dermatology, Oct.2008.
[24] Development of contactless motion tracking system for stereotactic radiosurgery Go Mamiya, Hitoshi Iyatomi, Koichi Ogawa Proc. 5th Korea-Japan joint meeting on medical physics, Cheju, Korea, SS1-R1-6, Sep.2008.
[23] An Internet-based Melanoma Screening System - Supported Acral Volar Lesions Hitoshi Iyatomi, M.Emre Celebi, Hiroshi Oka, Masaru Tanaka Proc. IEEE EMBC 2008, Vancouver, Canada, pp.5156-5159, Aug.2008. PDF (242KB)
[22] Objective Evaluation of Methods for Border Detection in Dermoscopy Images M.Emre Celebi, Gerald Schaefer, Hitoshi Iyatomi Proc. IEEE EMBC 2008, Vancouver, Canada, pp.3056-3059, Aug.2008. PDF (224KB)
[21] Identification of shot-body-regions from clinical photograph using support vector machine classifiers Hitoshi Iyatomi and Koichi Ogawa Proc. 10th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2007 Workshop), Brisbane, Australia, Oct.2007.
[20] Parametric Analysis of Acral Lesions on Dermoscopy Hitoshi Iyatomi, Hiroshi Oka, Masaru Tanaka and Koichi Ogawa Proc. of IEEE CME 2007, Beijin, China, pp.337-340, May.2007. PDF (185KB)
[19] Parameterization of Dermoscopic Findings for the Internet-based Melanoma Diagnostic System Hitoshi Iyatomi, Hiroshi Oka, M.Emre Celebi, Masaru Tanaka and Koichi Ogawa Proc.IEEE CIISP 2007, pp.183-193, Honolulu, Apr.2007. PDF(142KB)
[18] Fast and Accurate Border Detection in Dermoscopy Images Using Statistical Region Merging M. Emre Celebi, Hassan A. Kingravi, Hitoshi Iyatomi, JeongKyu Lee et al. Proc. SPIE Medical Imaging 2007 Conference, Feb.2007.
[17] Classification of Asian-specific acral lesions for internet-based melanoma diagnostic system Hitoshi Iyatomi, Hiroshi Oka, Masaru Tanaka and Koichi Ogawa Proc. Asian Medical Imaging Forum 2007, MI2006-183, pp.95-98, Cheju, Jan. 2007.
[16] Automatic Identification of Shot Body Region from Clinical Photographies Hitoshi Iyatomi, Masahiro Hashimoto, Hiroshi Oka, Masaru Tanaka and Koichi Ogawa Proc. IEEE 35th International Workshop on AIPR 2006, Washington DC, Oct. 2006.
[15] Classification of blue nevus from other lesions for Internet-based melanoma diagnostic system Hitoshi Iyatomi, Yuki Tanahashi, Hiroshi Oka, Masaru Tanaka and Koichi Ogawa Proc. 7th International Symposium on Advanced Intelligent Systems, Tokyo, pp.1995-2000, 2006.
[14] Portable VOG, a new device for on site nystagmus recording N.Ide, E.Sugiura, K.Miyajima, Y.Arai, H.Iyatomi and M.Yamamoto. 24th Barany Society Meeting, Uppsala, Sweden, Jun. 2006
[13] Current state of the Internet-based melanoma screening system Hitoshi Iyatomi, Hiroshi Oka, Masafumi Hagiwara, Masahiro Hashimoto,Koichi Ogawa, Masaru Tanaka First Congress of the International Dermoscopy Society, Naples, p.271, Apr.2006
[12] Hemifacial trial of vitamin C sonophoresis in melasma. Junko Kawashima, Shin-ichi Takahashi, Atsuko Katoh, Masaru Tanaka, Hitoshi Iyatomi, Hiroyuki Takano, Yasuhiro Sato. First Congress of the International Dermoscopy Society, Naples, Apr.27-29, 2006
[11] An Practical Internet-based Melanoma Diagnostic System Hitoshi Iyatomi, Hiroshi Oka, Ayako Miyake, Masayuki Kimoto Masaru Tanaka and Koichi Ogawa Proc. IEEE Symposium on CIBCB, pp.443-446, San Diego USA, Nov.2005. PDF (267KB)
[10] Preliminary study for quantification of psooriasis with color calibration Hitoshi Iyatomi, Hiroshi Oka, Ayako Miyake, Masayuki Kimoto Masaru Tanaka and Koichi Ogawa Proc. 4th Japan-Korea Joint Meeting on Medical Physics and the 5th Asia-Oceania Congress of Medical Physics, Kyoto, Japan, Sep.2005.
[9] Development of contactless motion tracking method for stereotactic radiosurgery Yuta Hojo, Hitoshi Iyatomi and Koichi Ogawa Proc. 4th Japan-Korea Joint Meeting on Medical Physics and the 5th Asia-Oceania Congress of Medical Physics, Kyoto, Japan, Sep.2005.
[8] Practical web-based screening system for early stage of malignant melanoma Hitoshi Iyatomi, Hiroshi Oka, Masaru Tanaka, Masafumi Hagiwara and Koichi Ogawa Proc. 3rd International Conference on Information (INFO2004), Tokyo, Japan, pp.628-631,Nov.2004
[7] Automatic tumor area extraction from dermoscopy image H.Iyatomi, H.Oka, M.Hashimoto, A.Tanikawa, M.Hagiwara and M.Tanaka Journal of European Academy of Dermatology and Venereology, Florence Italy, p.271, Oct.2004
[6] Development of diagnostic system for early stage of malignant melanoma Hitoshi Iyatomi, Hiroshi Oka, Masaru Tanaka and Masafumi Hagiwara Proc.5th International Symposium on Advanced Intelligent Systems, Yokohama, Japan, p.69, WE-4, Sep.2004.
[5] Additional Learning Machine Framework for Multipurpose Image Recognition Michiaki Itani, Hitoshi Iyatomi and Masafumi Hagiwara Proc.4th International Symposium on Advanced Intelligent Systems, Jeju Island, Korea, pp.480-pp.483, Sep.2003.
[4] Digital analysis of dermoscopy with multivariate stepwise discriminant analysis between early Melanoma and Nevi Oka H, Tanaka M, Kobayashi S, Iyatomi H, Hagiwara M, Argenziano G, Soyer H.P. and Nishikawa T. European congress of the EADV, Barcelona, Spain, Oct.2003.
[3] Classification of Reed/Spitz Nevi and Melanomas using digital image processing with linear discriminant analysis Kobayashi S, Tanaka M, Oka H, Iyatomi H, Hagiwara M, Argenziano G, Soyer H.P and Nishikawa T. European congress of the EADV, Barcelona, Spain, Oct.2003.
[2] Adaptive Fuzzy Inference Neural Network Hitoshi Iyatomi and Masafumi Hagiwara Proc. 10th International Conference on Human Computer Interaction 2003, Crete, Greece, Vol.2, pp.400-404.
[1] Knowledge Extraction from Scereny Images and the Recognition using Fuzzy Inference Neural Networks. Hitoshi Iyatomi and Masafumi Hagiwara IEEE International Conference on System Man and Cybernetics, San Diego, USA, pp.4486-4491, Oct.1998. PDF (480KBytes)