Search Results for author: Haoran Dou

Found 27 papers, 10 papers with code

Unsupervised Domain Adaptation for Brain Vessel Segmentation through Transwarp Contrastive Learning

1 code implementation23 Feb 2024 Fengming Lin, Yan Xia, Michael MacRaild, Yash Deo, Haoran Dou, Qiongyao Liu, Kun Wu, Nishant Ravikumar, Alejandro F. Frangi

Unsupervised domain adaptation (UDA) aims to align the labelled source distribution with the unlabelled target distribution to obtain domain-invariant predictive models.

Contrastive Learning Unsupervised Domain Adaptation

Learned Local Attention Maps for Synthesising Vessel Segmentations

no code implementations24 Aug 2023 Yash Deo, Rodrigo Bonazzola, Haoran Dou, Yan Xia, Tianyou Wei, Nishant Ravikumar, Alejandro F. Frangi, Toni Lassila

We present an encoder-decoder model for synthesising segmentations of the main cerebral arteries in the circle of Willis (CoW) from only T2 MRI.

Shape-guided Conditional Latent Diffusion Models for Synthesising Brain Vasculature

no code implementations13 Aug 2023 Yash Deo, Haoran Dou, Nishant Ravikumar, Alejandro F. Frangi, Toni Lassila

The Circle of Willis (CoW) is the part of cerebral vasculature responsible for delivering blood to the brain.

An Explainable Deep Framework: Towards Task-Specific Fusion for Multi-to-One MRI Synthesis

1 code implementation3 Jul 2023 Luyi Han, Tianyu Zhang, Yunzhi Huang, Haoran Dou, Xin Wang, Yuan Gao, Chunyao Lu, Tan Tao, Ritse Mann

Multi-sequence MRI is valuable in clinical settings for reliable diagnosis and treatment prognosis, but some sequences may be unusable or missing for various reasons.

GSMorph: Gradient Surgery for cine-MRI Cardiac Deformable Registration

1 code implementation26 Jun 2023 Haoran Dou, Ning Bi, Luyi Han, Yuhao Huang, Ritse Mann, Xin Yang, Dong Ni, Nishant Ravikumar, Alejandro F. Frangi, Yunzhi Huang

In this study, we construct a registration model based on the gradient surgery mechanism, named GSMorph, to achieve a hyperparameter-free balance on multiple losses.

Fourier Test-time Adaptation with Multi-level Consistency for Robust Classification

no code implementations5 Jun 2023 Yuhao Huang, Xin Yang, Xiaoqiong Huang, Xinrui Zhou, Haozhe Chi, Haoran Dou, Xindi Hu, Jian Wang, Xuedong Deng, Dong Ni

Second, we introduce a regularization technique that utilizes style interpolation consistency in the frequency space to encourage self-consistency in the logit space of the model output.

Robust classification Test-time Adaptation

A Generative Shape Compositional Framework to Synthesise Populations of Virtual Chimaeras

no code implementations4 Oct 2022 Haoran Dou, Seppo Virtanen, Nishant Ravikumar, Alejandro F. Frangi

Specifically, we propose a generative shape compositional framework which comprises two components - a part-aware generative shape model which captures the variability in shape observed for each structure of interest in the training population; and a spatial composition network which assembles/composes the structures synthesised by the former into multi-part shape assemblies (viz.

Anatomy Self-Supervised Learning +1

Localizing the Recurrent Laryngeal Nerve via Ultrasound with a Bayesian Shape Framework

1 code implementation30 Jun 2022 Haoran Dou, Luyi Han, Yushuang He, Jun Xu, Nishant Ravikumar, Ritse Mann, Alejandro F. Frangi, Pew-Thian Yap, Yunzhi Huang

Tumor infiltration of the recurrent laryngeal nerve (RLN) is a contraindication for robotic thyroidectomy and can be difficult to detect via standard laryngoscopy.

Deformable Registration of Brain MR Images via a Hybrid Loss

no code implementations28 Oct 2021 Luyi Han, Haoran Dou, Yunzhi Huang, Pew-Thian Yap

Unsupervised learning strategy is widely adopted by the deformable registration models due to the lack of ground truth of deformation fields.

A Deep Attentive Convolutional Neural Network for Automatic Cortical Plate Segmentation in Fetal MRI

2 code implementations27 Apr 2020 Haoran Dou, Davood Karimi, Caitlin K. Rollins, Cynthia M. Ortinau, Lana Vasung, Clemente Velasco-Annis, Abdelhakim Ouaalam, Xin Yang, Dong Ni, Ali Gholipour

Automatic segmentation of the cortical plate, on the other hand, is challenged by the relatively low resolution of the reconstructed fetal brain MRI scans compared to the thin structure of the cortical plate, partial voluming, and the wide range of variations in the morphology of the cortical plate as the brain matures during gestation.

Segmentation

Agent with Warm Start and Active Termination for Plane Localization in 3D Ultrasound

1 code implementation10 Oct 2019 Haoran Dou, Xin Yang, Jikuan Qian, Wufeng Xue, Hao Qin, Xu Wang, Lequan Yu, Shujun Wang, Yi Xiong, Pheng-Ann Heng, Dong Ni

In this study, we propose a novel reinforcement learning (RL) framework to automatically localize fetal brain standard planes in 3D US.

Reinforcement Learning (RL)

Joint Segmentation and Landmark Localization of Fetal Femur in Ultrasound Volumes

no code implementations31 Aug 2019 Xu Wang, Xin Yang, Haoran Dou, Shengli Li, Pheng-Ann Heng, Dong Ni

In this paper, we propose an effective framework for simultaneous segmentation and landmark localization in prenatal ultrasound volumes.

Segmentation

Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound

1 code implementation3 Jul 2019 Yi Wang, Haoran Dou, Xiao-Wei Hu, Lei Zhu, Xin Yang, Ming Xu, Jing Qin, Pheng-Ann Heng, Tianfu Wang, Dong Ni

Our attention module utilizes the attention mechanism to selectively leverage the multilevel features integrated from different layers to refine the features at each individual layer, suppressing the non-prostate noise at shallow layers of the CNN and increasing more prostate details into features at deep layers.

Image Segmentation Medical Image Segmentation +2

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