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20212024
most citedDomain Generalization for Prostate Segmentation in Transrectal Ultrasound Images: A Multi-center Study

2 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

eess.IV2024★ 1 cited

Poisson Ordinal Network for Gleason Group Estimation Using Bi-Parametric MRI

Yinsong Xu, Yipei Wang, Ziyi Shen +7

The Gleason groups serve as the primary histological grading system for prostate cancer, providing crucial insights into the cancer's potential for growth and metastasis. In clinic…

cs.CV2024

Competing for pixels: a self-play algorithm for weakly-supervised segmentation

Shaheer U. Saeed, Shiqi Huang, João Ramalhinho +8

Weakly-supervised segmentation (WSS) methods, reliant on image-level labels indicating object presence, lack explicit correspondence between labels and regions of interest (ROIs),…

eess.IV2024

Semi-weakly-supervised neural network training for medical image registration

Yiwen Li, Yunguan Fu, Iani J. M. B. Gayo +11

For training registration networks, weak supervision from segmented corresponding regions-of-interest (ROIs) have been proven effective for (a) supplementing unsupervised methods,…

eess.IV2022★ 2 cited

Domain Generalization for Prostate Segmentation in Transrectal Ultrasound Images: A Multi-center Study

Sulaiman Vesal, Iani Gayo, Indrani Bhattacharya +7

Prostate biopsy and image-guided treatment procedures are often performed under the guidance of ultrasound fused with magnetic resonance images (MRI). Accurate image fusion relies…

cs.LG2022

Strategising template-guided needle placement for MR-targeted prostate biopsy

Iani JMB Gayo, Shaheer U. Saeed, Dean C. Barratt +2

Clinically significant prostate cancer has a better chance to be sampled during ultrasound-guided biopsy procedures, if suspected lesions found in pre-operative magnetic resonance…

cs.CV2021

Development and evaluation of intraoperative ultrasound segmentation with negative image frames and multiple observer labels

Liam F Chalcroft, Jiongqi Qu, Sophie A Martin +8

When developing deep neural networks for segmenting intraoperative ultrasound images, several practical issues are encountered frequently, such as the presence of ultrasound frames…