Shimizu Laboratory

Shimizu Lab.

Researches on medical image analysis based on the state of the art technologies of pattern recognition, machine learning, artificial intelligence, and big data analysis.

Development of computer-aided diagnosis systems using the research results.

    Atsushi Saito, Masaki Tsujikawa, Tetsuya Takakuwa, Shigehito Yamada,
    Akinobu Shimizu

    Level set distribution model of nested structures using logarithmic transformation

    Medical Image Analysis, 56, 1-10, 2019
    10.1016/j.media.2019.05.003

    Shouhei Hanaoka, Akinobu Shimizu, Mitsutaka Nemoto, Yukihiro Nomura, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Kuni Ohtomo, Yoshitaka Masutani

    Automatic detection of over 100 anatomical landmarks in medical CT images: A framework with independent detectors and combinatorial optimization

    Medical Image Analysis, 35, 192-214, 2016
    10.1016/j.media.2016.04.001

    Atsushi Saito,
    Shigeru Nawano and Akinobu Shimizu

    Joint optimization of segmentation and shape prior from level-set-based statistical shape model, and its application to the automated segmentation of abdominal organs

    Medical Image Analysis, 28, 46-65, 2016
    10.1016/j.media.2015.11.003

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Recent posts

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on April 17, 2026

March 2, 2026
A fourth-year undergraduate, Andrews, spent one month studying abroad in Freiburg, Germany, as part of an international collaborative research project under Hahn-Schickard and Dr. Cypko at the University of Freiburg.

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on March 21, 2025

March 21, 2025
・Wakao(M2), Kadono(B4), Sasaki(B4), Kubo(B4), Hiratsuka(B4), Hirose(B4), and Fujii(B4) presented at IFMIA2025@Kagawa International Conference Hall.

Kubo(B4) and Fujii(B4) received the Poster Award.

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on October 24, 2024

October 24, 2024
・HE Minxuan, students in the second year of the master’s program at the Technische Universität München, Germany, visited our laboratory for a six-month internship.

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on October 10, 2024

October 10, 2024
・Ms. QUYNH ANH NGUYEN (First year PhD student) presented the following research at MICCAI2024-workshop(TGI3)＠Marrākish(Morocco)
Multi-Factor Component Tree Loss Function: A Topology-Preserving Method for Skeleton Segmentation from Bone Scintigrams

Previous posts

To Applicants

Medical image analysis laboratory has collaborated with many universities, public research institutions, and companies. In 2019, we have collaborated with universities (the University of Tokyo etc.), two public institutions (RIKEN etc.), overseas universities (ESIEE Paris(France) etc.) and research institutions (Children’s National Health System(USA)), and other domestic companies. Knowledge of programming languages, AI, mathematics (linear algebra, mathematical analysis, statistical mathematics), signal processing is required to conduct the researches in our lab. If you are interested in medical image analysis and/or collaboration with our research partners, please visit our laboratory.