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eess.IV2025

TUS-REC2024: A Challenge to Reconstruct 3D Freehand Ultrasound Without External Tracker

Qi Li, Shaheer U. Saeed, Yuliang Huang +24

Trackerless freehand ultrasound reconstruction aims to reconstruct 3D volumes from sequences of 2D ultrasound images without relying on external tracking systems. By eliminating th…

eess.IV2025

A versatile foundation model for cine cardiac magnetic resonance image analysis tasks

Yunguan Fu, Wenjia Bai, Weixi Yi +7

Here we present a versatile foundation model that can perform a range of clinically-relevant image analysis tasks, including segmentation, landmark localisation, diagnosis, and pro…

eess.IV2025

Promptable cancer segmentation using minimal expert-curated data

Lynn Karam, Yipei Wang, Veeru Kasivisvanathan +3

Automated segmentation of cancer on medical images can aid targeted diagnostic and therapeutic procedures. However, its adoption is limited by the high cost of expert annotations r…

eess.IV2024

T2-Only Prostate Cancer Prediction by Meta-Learning from Bi-Parametric MR Imaging

Weixi Yi, Yipei Wang, Natasha Thorley +6

Current imaging-based prostate cancer diagnosis requires both MR T2-weighted (T2w) and diffusion-weighted imaging (DWI) sequences, with additional sequences for potentially greater…

eess.IV2024

AI-assisted prostate cancer detection and localisation on biparametric MR by classifying radiologist-positives

Xiangcen Wu, Yipei Wang, Qianye Yang +5

Prostate cancer diagnosis through MR imaging have currently relied on radiologists' interpretation, whilst modern AI-based methods have been developed to detect clinically signific…

eess.IV2024

Nonrigid Reconstruction of Freehand Ultrasound without a Tracker

Qi Li, Ziyi Shen, Qianye Yang +4

Reconstructing 2D freehand Ultrasound (US) frames into 3D space without using a tracker has recently seen advances with deep learning. Predicting good frame-to-frame rigid transfor…