Zobrazeno 1 - 10
of 1 246
pro vyhledávání: '"P. Emberton"'
Autor:
Min, Zhe, Baum, Zachary M. C., Saeed, Shaheer U., Emberton, Mark, Barratt, Dean C., Taylor, Zeike A., Hu, Yipeng
This paper investigates both biomechanical-constrained non-rigid medical image registrations and accurate identifications of material properties for soft tissues, using physics-informed neural networks (PINNs). The complex nonlinear elasticity theory
Externí odkaz:
http://arxiv.org/abs/2407.03292
Autor:
Pocius, Martynas, Yan, Wen, Barratt, Dean C., Emberton, Mark, Clarkson, Matthew J., Hu, Yipeng, Saeed, Shaheer U.
In this paper we propose a reinforcement learning based weakly supervised system for localisation. We train a controller function to localise regions of interest within an image by introducing a novel reward definition that utilises non-binarised cla
Externí odkaz:
http://arxiv.org/abs/2402.13778
Autor:
Li, Yiwen, Fu, Yunguan, Gayo, Iani J. M. B., Yang, Qianye, Min, Zhe, Saeed, Shaheer U., Yan, Wen, Wang, Yipei, Noble, J. Alison, Emberton, Mark, Clarkson, Matthew J., Barratt, Dean C., Prisacariu, Victor A., Hu, Yipeng
For training registration networks, weak supervision from segmented corresponding regions-of-interest (ROIs) have been proven effective for (a) supplementing unsupervised methods, and (b) being used independently in registration tasks in which unsupe
Externí odkaz:
http://arxiv.org/abs/2402.10728
Autor:
Yan, Wen, Chiu, Bernard, Shen, Ziyi, Yang, Qianye, Syer, Tom, Min, Zhe, Punwani, Shonit, Emberton, Mark, Atkinson, David, Barratt, Dean C., Hu, Yipeng
Publikováno v:
journal={Medical Image Analysis}, volume={91}, pages={103030}, year={2024}, publisher={Elsevier}
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 modalities, T2-weighted, diffusion-weighted, and dynamic contrast-enha
Externí odkaz:
http://arxiv.org/abs/2307.08279
Autor:
Hannah Warren, Jack B. Fanshawe, Valerie Mok, Priyanka Iyer, Vinson Wai‐Shun Chan, Richard Hesketh, Eleanor Zimmermann, Veeru Kasivisvanathan, Mark Emberton, Maxine G. B. Tran, Kurinchi Gurusamy
Publikováno v:
BJUI Compass, Vol 5, Iss 7, Pp 636-650 (2024)
Abstract Objectives International guidelines recommend resection of suspected localised renal cell carcinoma (RCC), with surgical series showing benign pathology in 30%. Non‐invasive diagnostic tests to differentiate benign from malignant tumours a
Externí odkaz:
https://doaj.org/article/3518b07696cd41dd8302179186fb2471
Autor:
Lu, Yaozhi, Aslani, Shahab, Zhao, An, Shahin, Ahmed, Barber, David, Emberton, Mark, Alexander, Daniel C., Jacob, Joseph
In this study, we present a hybrid CNN-RNN approach to investigate long-term survival of subjects in a lung cancer screening study. Subjects who died of cardiovascular and respiratory causes were identified whereby the CNN model was used to capture i
Externí odkaz:
http://arxiv.org/abs/2303.10789
Autor:
Saeed, Shaheer U., Syer, Tom, Yan, Wen, Yang, Qianye, Emberton, Mark, Punwani, Shonit, Clarkson, Matthew J., Barratt, Dean C., Hu, Yipeng
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-parametric images conditioned on images e.g. for generating diffusion-weighte
Externí odkaz:
http://arxiv.org/abs/2303.02094
Autor:
Min, Zhe, Baum, Zachary M. C., Saeed, Shaheer U., Emberton, Mark, Barratt, Dean C., Taylor, Zeike A., Hu, Yipeng
Biomechanical modelling of soft tissue provides a non-data-driven method for constraining medical image registration, such that the estimated spatial transformation is considered biophysically plausible. This has not only been adopted in real-world c
Externí odkaz:
http://arxiv.org/abs/2302.10343
Autor:
Lara Rodríguez-Sánchez, Mark Emberton, Theo de Reijke, Phillip Stricker, Bernardino Miñana, Fernando Bianco, Jose Luis Dominguez Escrig, Anna Lantz, Rafael Sanchez-Salas
Publikováno v:
The World Journal of Men's Health, Vol 42, Iss 2, Pp 245-255 (2024)
Externí odkaz:
https://doaj.org/article/69e65c0b914141d98d626e1849783d3a
Autor:
Li, Yiwen, Fu, Yunguan, Gayo, Iani, Yang, Qianye, Min, Zhe, Saeed, Shaheer, Yan, Wen, Wang, Yipei, Noble, J. Alison, Emberton, Mark, Clarkson, Matthew J., Huisman, Henkjan, Barratt, Dean, Prisacariu, Victor Adrian, Hu, Yipeng
The prowess that makes few-shot learning desirable in medical image analysis is the efficient use of the support image data, which are labelled to classify or segment new classes, a task that otherwise requires substantially more training images and
Externí odkaz:
http://arxiv.org/abs/2209.05160