Posts
CAI4CAI members are leading the organization of the cross-modality Domain Adaptation challenge (crossMoDA) for medical image segmentation Challenge, which runs as an official challenge during the Medical Image Computing and Computer Assisted Interventions (MICCAI) 2021 conference.
King’s College London, School of Biomedical Engineering & Imaging Sciences and Moon Surgical announced a new strategic partnership to develop Machine Learning applications for Computer-Assisted Surgery, which aims to strengthen surgical artificial intelligence (AI), data and analytics, and accelerate translation from King’s College London research into clinical usage.
Yijing will develop a 3D functional optical imaging system for guiding brain tumour resection.
She will engineer two emerging modalities, light field and multispectral imaging into a compact device, and develop novel image reconstruction algorithm to produce and display high-dimensional images. The CME fellowship will support her to carry out proof-of-concept studies, start critical new collaborations within and outside the centre. She hopes the award will act as a stepping stone to enable future long-term fellowship and grants, thus to establish an independent research programme.
Miguel will collaborate with Fang-Yu Lin and Shu Wang to create activities to engage school students with ultrasound-guidance intervention and fetal medicine. In the FETUS project, they will develop interactive activities with 3D-printed fetus, placenta phantoms as well as the integreation of a simulator that explain principles of needle enhancement of an ultrasound needle tracking system.
A great milestone today for Luis Garcia Peraza Herrera who passed his PhD viva with minor corrections! His thesis is entitled “Deep Learning for Real-time Image Understanding in Endoscopic Vision”.
Thanks to Ben Glocker and Enrico Grisan for their role examining the thesis.
