activity
20172026
most citedWeakly-Supervised Convolutional Neural Networks for Multimodal Image Registration

477 citations · 994 across the 58 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

eess.IV2023★ 20 cited

Long-term Dependency for 3D Reconstruction of Freehand Ultrasound Without External Tracker

Qi Li, Ziyi Shen, Qian Li +5

Objective: Reconstructing freehand ultrasound in 3D without any external tracker has been a long-standing challenge in ultrasound-assisted procedures. We aim to define new ways of…

cs.CV2023

Boundary-RL: Reinforcement Learning for Weakly-Supervised Prostate Segmentation in TRUS Images

Weixi Yi, Vasilis Stavrinides, Zachary M. C. Baum +5

We propose Boundary-RL, a novel weakly supervised segmentation method that utilises only patch-level labels for training. We envision the segmentation as a boundary detection probl…

cs.CV2023★ 1 cited

Privileged Anatomical and Protocol Discrimination in Trackerless 3D Ultrasound Reconstruction

Qi Li, Ziyi Shen, Qian Li +5

Three-dimensional (3D) freehand ultrasound (US) reconstruction without using any additional external tracking device has seen recent advances with deep neural networks (DNNs). In t…

eess.IV2023★ 7 cited

Combiner and HyperCombiner Networks: Rules to Combine Multimodality MR Images for Prostate Cancer Localisation

Wen Yan, Bernard Chiu, Ziyi Shen +8

One of the distinct characteristics in radiologists' reading of multiparametric prostate MR scans, using reporting systems such as PI-RADS v2.1, is to score individual types of MR…

eess.IV2023★ 7 cited

Bi-parametric prostate MR image synthesis using pathology and sequence-conditioned stable diffusion

Shaheer U. Saeed, Tom Syer, Wen Yan +6

We propose an image synthesis mechanism for multi-sequence prostate MR images conditioned on text, to control lesion presence and sequence, as well as to generate paired bi-paramet…

eess.IV2023

Non-rigid Medical Image Registration using Physics-informed Neural Networks

Zhe Min, Zachary M. C. Baum, Shaheer U. Saeed +4

Biomechanical modelling of soft tissue provides a non-data-driven method for constraining medical image registration, such that the estimated spatial transformation is considered b…