In the biological research, cell and molecular level biological phenomena are observed as 2D and 4D(3D+time) images by new imaging technologies to elucidate the principle of biological phenomena. In such research, quantitative and data analysis technologies for the biological images captured in a state similar to in vivo are important. However, in vivo, observation targets such as cells and molecules are distributed in a high density. This makes it difficult to quantify the metrics of behaviors and shapes from such images, and this is critical in biological research.
In this research, we are developing multi-object tracking methods for realizing robustness and versatility in high density, and we will apply the tracking methods and data analysis techniques to analyze the behaviors of cells and molecules. This makes the objective data analysis and scale up to big data easy. Our goal is to contribute to innovation in the biological field by developing such tracking methods and data analysis techniques.
2020
Hayashida J., Nishimura K., Bise R. (2020) MPM: Joint Representation of Motion and Position Map for Cell Tracking. IEEE CVPR2020, 3823-3832.
2019
Hayashida J., Bise R. (2019) Cell Tracking with Deep Learning for Cell Detection and Motion Estimation in Low-Frame-Rate. In: Shen D. et al. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. MICCAI 2019. Lecture Notes in Computer Science, vol 11764. Springer, Cham.
doi: 10.1007/978-3-030-32239-7_44.
2017
Chen Q., Bise R., Gu L., Zheng Y., Sato I., Hwang J.N., Imanishi N., Aiso S. (2017) Virtual Blood Vessels in Complex Background using Stereo X-ray Images. ICCV Workshop, BioImage Computing, 99-106.
doi: 10.1109/ICCVW.2017.20.
Gu L., Zheng Y., Bise R., Sato I., Imanishi N., Aiso S. (2017) Semi-supervised Learning for Biomedical Image Segmentation via Forest Oriented Super Pixels(Voxels). In: Descoteaux M., Maier-Hein L., Franz A., Jannin P., Collins D., Duchesne S. (eds) Medical Image Computing and Computer Assisted Intervention − MICCAI 2017. MICCAI 2017. Lecture Notes in Computer Science, vol 10433: pp.702-710, Springer, Cham.
doi: 10.1007/978-3-319-66182-7_80.
Shimano M., Bise R., Zheng Y., Sato I. (2017) Separation of Transmitted Light and Scattering Components in Transmitted Microscopy. In: Descoteaux M., Maier-Hein L., Franz A., Jannin P., Collins D., Duchesne S. (eds) Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017. MICCAI 2017. Lecture Notes in Computer Science, vol 10434: pp.702-710, Springer, Cham.
doi: 10.1007/978-3-319-66185-8_2.
Shimano M., Okawa H., Asano Y., Bise R., Nishino K., Sato I. (2017) Wetness and Color from a Single Multispectral Image. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 321-329.
doi: 10.1109/CVPR.2017.42.
