FY2021
画像情報処理研究チーム ／ Image Processing Research Team（１） 原著論⽂ (accept) を含む ／ Original Papers
1. Hu, R., Monebhurrun, V., Himeno, R., Yokota, H., and Costen, F.: “A general framework
for building surrogate models for uncertainty quantification in computationalelectromagnetics”, IEEE Transaction on Antennas and Propagation Vol.70, pp.1402-1414(2022).
2. Takematsu, M., Umezawa, M., Sera, T., Kitagawa, Y., Kurahashi, H., Yamada, S., Okubo,
K., Kamimura, M., Yokota, H., and Soga, K.: “Influence of the difference in refractive
index on the interface of an object and the surrounding in near-infrared fluorescence
tomography”, Applied Optics (2021).
3. Michikawa, T., Yoshida, T., Kuroki, S., Ishikawa, T., Kakei, S., Kimizuka, R., Saito, A.,Yokota, H., Shimizu, A., Itohara, S., and Miyawaki, A.: “Distributed sensory coding by
cerebellar complex spikes in units of cortical segments”, Cell Reports 37,6 (2021).
4. Xanthos, L., Yavuz, M. E., Himeno, R., Yokota, H., and Costen, F.: “Resolution
Enhancement of UWB Time-Reversal Microwave Imaging in Dispersive Environments”,
IEEE Transactions on Computational Imaging. Vol.7, pp.925-934 (2021).
5. Chen, M., Wu, J., Li, S., Liu, J., Yokota, H., and Guo, S.: “Accurate and real-time humanjoint-position estimation for a patient-transfer robot using a two-level convolutional
neutral network”, Robotics and Autonomous Systems 139(1), 103735 (2021).
6. Takamatsu, T., Kitagawa, Y., Akimoto, K., Iwanami, R., Endo, Y., Takashima, K., Okubo,K., Umezawa, M., Kuwata, T., Sato, D., Kadota, T., Mitsui, T., Ikematsu, H., Yokota, H.,Soga, K., and Takemura, H.: “Over 1000 nm Near-Infrared Multispectral Imaging Systemfor Laparoscopic In Vivo Imaging”, Sensors 21(8), 2649 (2021).
7. Sonoda, S., Shiihara, H., Terasaki, H., Kakiuchi, N., Funatsu, R., Tomita, M., Shinohara,Y., Uchino, E., Udagawa, T., An, G., Akiba, M., Yokota, H., and Sakamoto, T.: “Artificialintelligence for classifying uncertain images by humans in determining choroidal vascularrunning pattern and comparisons with automated classification between artificialintelligence”, PLOS ONE (2021).
8. An, G., Aloba, M., Omodaka, K., Nakazawa, T., and Yokota, H.: “Hierarchical deep learningmodels using transfer learning for disease detection and classification based on small
number of medical images”, Scientific Reports (2021).
9. Yoshizawa, S., and Yokota H.: “Fast and faithful scale-aware image filters”, The VisualComputer Vol. 37, Issue 12, pp. 3051‒3062 (2021).

10. Takahashi, K., Sun, Z., Solé-Casals, J., Cichocki, A., Huy Phan, A., Zhao, Q., Zhao, H.,Deng, S., and Micheletto, R.: “Data Augmentation For Convolutional LSTM based BrainComputer Interface System”, Applied Soft Computing (2022).
11. Yamashita, N., Matsuno, T., Maeda, D., Kikuzuki, M., and Yokota, H.: “Efficient 3D
observation of steel microstructure using serial 49 sectioning with precision cutting andon-site etching”, Precision Engineering Vol. 75, pp. 37-45 (2022).
12. ⽵本智⼦, 吉澤信, ⼭下典理男, 森⽥正彦, ⻄村将⾂, 横⽥ 秀夫: “ 画像処理による細胞集団の形態と機能の定量解析”, Drug Delivery System Vol. 36, No.4, pp. 277-285(2021).
13. Fujisaki, K., Yamashita, N., and Yokota, H.: “Multipoint indentation for materialidentification in three-dimensional observation based on serial sectioning”, Precision
Engineering Vol. 69, pp. 62-67 (2021).
14. Hori, K., Ikematsu, H., Yamamoto, Y., Matsuzaki, H., Takeshita, N., Shinmura, K., Yoda,
Y., Kiuchi, T., Takemoto, S., Yokota, H., and Yano, T.: “Detecting colon polyps inendoscopic images using artificial intelligence constructed with automated collection ofannotated images from an endoscopy reporting system”, Digestive endoscopy (2021).
15. Kitrungrotsakul, T., Han, X-X., Iwamoto, Y., Takemoto, S., Yokota, H., Ipponjima, S.,Nemoto, T., Wei, X., and Chen, Y.-W.: “A Cascade of 2.5D CNN and Bidirectional
CLSTM Network for Mitotic Cell Detection in 4D Microscopy Image”, IEEE/ACM
Transactions on Computational Biology and Bioinformatics vol. 18, no. 2, pp. 396-404(2021).
16. Kitrungrotsakul, T., Iwamoto, Y., Takemoto, S., Yokota, H., Ipponjima, S., Nemoto, T.,
Lin, L., Tong, R., Li,J., and Chen, T.-W.: “Accurate and fast mitotic detection using ananchor-free method based on full-scale connection with recurrent deep layer aggregationin 4D microscopy images”, BMC Bioinformatics Vol. 22, Article number: 91 (2021).
17. 堀圭介, ⽵本智⼦, 横⽥秀夫, 池松弘朗, ⽮野友規, “ ⾼効率な学習スキームによる胃癌の領域検出 AI”, 胃と腸 Vol. 56(4), 423-431(2021).
（２） 招待講演 ／ Invited Talks
1. Sun, Z., “ スーパーコン富岳に基づく脳シミュレーション”, 静岡⼤学テニュアトラック
浜松セミナー, (2021).
（３） 会議、シンポジウム、セミナー主催 ／ Meeting, Symposiums and Seminars
1. 精密⼯学会 外観検査アルゴリズムコンテスト共催, オンライン, 12 ⽉（2021）.

（４） 特許出願 ／ Patent Applications
1. 深堀昴, 梶⾕ケビン, 筒雅博, フェルナンドチャリス・ラサンサ, 孫哲, 吉澤信, 道川隆⼠,
横⽥秀夫, “ 画像処理システム、画像エンコーダ、画像デコーダ、画像処理⽅法及び画像処理プログラム”, 特願 2021-028581, 2021 年 3 ⽉ 25 ⽇.
2. 深堀昴, 梶⾕ケビン, 筒雅博, フェルナンドチャリス・ラサンサ, 孫哲, 吉澤信, 道川隆⼠,横⽥秀夫, “ 画像符号化装置、画像符号化⽅法、画像復号化装置、及び画像復号化⽅法”,
特願 2021-028534, 2021 年 3 ⽉ 25 ⽇.
3. 深堀昴, 梶⾕ケビン, 筒雅博, フェルナンドチャリス・ラサンサ, 孫哲, 吉澤信, 道川隆⼠,横⽥秀夫, “ 画像符号化装置、画像符号化⽅法、画像復号化装置、及び画像復号化⽅法”,
特願 2021-028459, 2021 年 3 ⽉ 25 ⽇.
4. 和⽥智之, 佐々⾼史, 道川隆⼠, 国本幸弘, 重⽥将宏, “ 異常⾳判定⽅法、異常⾳判定プログラム及び異常⾳判定システム”, 特願 2021-158823, 2021 年.