no code implementations • 27 Oct 2022 • Zachary M. C. Baum, Yipeng Hu, Dean Barratt
We present a meta-learning framework for interactive medical image registration.
1 code implementation • 12 Sep 2022 • Yiwen Li, Yunguan Fu, Iani Gayo, Qianye Yang, Zhe Min, Shaheer Saeed, Wen Yan, Yipei Wang, J. Alison Noble, Mark Emberton, Matthew J. Clarkson, Henkjan Huisman, Dean Barratt, Victor Adrian Prisacariu, Yipeng Hu
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 expert annotations.
no code implementations • 13 Jul 2022 • Ziyi Shen, Qianye Yang, Yuming Shen, Francesco Giganti, Vasilis Stavrinides, Richard Fan, Caroline Moore, Mirabela Rusu, Geoffrey Sonn, Philip Torr, Dean Barratt, Yipeng Hu
Image registration is useful for quantifying morphological changes in longitudinal MR images from prostate cancer patients.
no code implementations • 17 Jan 2022 • Yiwen Li, Yunguan Fu, Qianye Yang, Zhe Min, Wen Yan, Henkjan Huisman, Dean Barratt, Victor Adrian Prisacariu, Yipeng Hu
The ability to adapt medical image segmentation networks for a novel class such as an unseen anatomical or pathological structure, when only a few labelled examples of this class are available from local healthcare providers, is sought-after.
no code implementations • 4 Jun 2021 • Zhe Min, Fernando J. Bianco, Qianye Yang, Rachael Rodell, Wen Yan, Dean Barratt, Yipeng Hu
Prostate cancer (PCa) is one of the leading causes of death for men worldwide.
no code implementations • 16 Jan 2021 • Qianye Yang, Tom Vercauteren, Yunguan Fu, Francesco Giganti, Nooshin Ghavami, Vasilis Stavrinides, Caroline Moore, Matt Clarkson, Dean Barratt, Yipeng Hu
Organ morphology is a key indicator for prostate disease diagnosis and prognosis.
no code implementations • 6 Oct 2020 • Alexander Grimwood, Helen McNair, Yipeng Hu, Ester Bonmati, Dean Barratt, Emma Harris
For images with unanimous consensus between observers, anatomical classification accuracy was 97. 2% and probe adjustment accuracy was 94. 9%.
no code implementations • 29 Aug 2020 • Qianye Yang, Yunguan Fu, Francesco Giganti, Nooshin Ghavami, Qingchao Chen, J. Alison Noble, Tom Vercauteren, Dean Barratt, Yipeng Hu
Morphological analysis of longitudinal MR images plays a key role in monitoring disease progression for prostate cancer patients, who are placed under an active surveillance program.
no code implementations • 18 Dec 2017 • Ester Bonmati, Yipeng Hu, Nikhil Sindhwani, Hans Peter Dietz, Jan D'hooge, Dean Barratt, Jan Deprest, Tom Vercauteren
Results show a median Dice similarity coefficient of 0. 90 with an interquartile range of 0. 08, with equivalent performance to the three operators (with a Williams' index of 1. 03), and outperforming a U-Net architecture without the need for batch normalisation.