Zobrazeno 1 - 10
of 134
pro vyhledávání: '"Ye, Xujiong"'
Imaging mass cytometry (IMC) is a relatively new technique for imaging biological tissue at subcellular resolution. In recent years, learning-based segmentation methods have enabled precise quantification of cell type and morphology, but typically re
Externí odkaz:
http://arxiv.org/abs/2402.04446
Besides the complex nature of colonoscopy frames with intrinsic frame formation artefacts such as light reflections and the diversity of polyp types/shapes, the publicly available polyp segmentation training datasets are limited, small and imbalanced
Externí odkaz:
http://arxiv.org/abs/2211.02416
Autor:
Nwokedi, Ezechukwu I., Bains, Rasneer S., Bidaut, Luc, Ye, Xujiong, Wells, Sara, Brown, James M.
This paper presents a spatiotemporal deep learning approach for mouse behavioural classification in the home-cage. Using a series of dual-stream architectures with assorted modifications to increase performance, we introduce a novel feature sharing a
Externí odkaz:
http://arxiv.org/abs/2206.00614
Autor:
Nwokedi, Ezechukwu I, Bains, Rasneer S, Bidaut, Luc, Wells, Sara, Ye, Xujiong, Brown, James M
This paper explores the application of unsupervised learning to detecting anomalies in mouse video data. The two models presented in this paper are a dual-stream, 3D convolutional autoencoder (with residual connections) and a dual-stream, 2D convolut
Externí odkaz:
http://arxiv.org/abs/2106.00598
Publikováno v:
BrainLes 2020. Lecture Notes in Computer Science, vol 12659, pp 410-419
In this paper we propose a 2D deep residual Unet with 104 convolutional layers (DR-Unet104) for lesion segmentation in brain MRIs. We make multiple additions to the Unet architecture, including adding the 'bottleneck' residual block to the Unet encod
Externí odkaz:
http://arxiv.org/abs/2011.02840
Autor:
Azarmehr, Neda, Ye, Xujiong, Janan, Faraz, Howard, James P, Francis, Darrel P, Zolgharni, Massoud
Publikováno v:
MIDL/2019/ExtendedAbstract/Sye8klvmcN; MyUni-UID
Following the successful application of the U-Net to medical images, there have been different encoder-decoder models proposed as an improvement to the original U-Net for segmenting echocardiographic images. This study aims to examine the performance
Externí odkaz:
http://arxiv.org/abs/2003.07628
Autor:
Soltaninejad, Mohammadreza, Zhang, Lei, Lambrou, Tryphon, Yang, Guang, Allinson, Nigel, Ye, Xujiong
Publikováno v:
In Proceeding of 2017 International MICCAI BraTS Challenge, pp. 279-283 (2017)
In this paper, we propose a novel learning based method for automated segmentation of brain tumor in multimodal MRI images, which incorporates two sets of machine -learned and hand crafted features. Fully convolutional networks (FCN) forms the machin
Externí odkaz:
http://arxiv.org/abs/1909.06337
Publikováno v:
European Journal of Operational Research, 281(3): 532-542, 2020
One trend in the recent healthcare transformations is people are encouraged to monitor and manage their health based on their daily diets and physical activity habits. However, much attention of the use of operational research and analytical models i
Externí odkaz:
http://arxiv.org/abs/1905.10891
Individual pig detection and tracking is an important requirement in many video-based pig monitoring applications. However, it still remains a challenging task in complex scenes, due to problems of light fluctuation, similar appearances of pigs, shap
Externí odkaz:
http://arxiv.org/abs/1812.04901
Autor:
Amer, Alyaa, Ye, Xujiong
Publikováno v:
In Computer Methods and Programs in Biomedicine Update 2023 4
