Search Results for author: Xiaowei Ding

Found 9 papers, 1 papers with code

MDT-Net: Multi-domain Transfer by Perceptual Supervision for Unpaired Images in OCT Scan

no code implementations12 Mar 2022 Weinan Song, Gaurav Fotedar, Nima Tajbakhsh, Ziheng Zhou, Xiaowei Ding

We also take the transformed results as additional training images for fluid segmentation in OCT scans in the tasks of domain adaptation and data augmentation.

Data Augmentation Domain Adaptation

A Location-Sensitive Local Prototype Network for Few-Shot Medical Image Segmentation

1 code implementation18 Mar 2021 Qinji Yu, Kang Dang, Nima Tajbakhsh, Demetri Terzopoulos, Xiaowei Ding

Despite the tremendous success of deep neural networks in medical image segmentation, they typically require a large amount of costly, expert-level annotated data.

Medical Image Segmentation Semantic Segmentation

Extreme Consistency: Overcoming Annotation Scarcity and Domain Shifts

no code implementations15 Apr 2020 Gaurav Fotedar, Nima Tajbakhsh, Shilpa Ananth, Xiaowei Ding

In this paper, we introduce \emph{extreme consistency}, which overcomes the above limitations, by maximally leveraging unlabeled data from the same or a different domain in a teacher-student semi-supervised paradigm.

Retinal Vessel Segmentation

ErrorNet: Learning error representations from limited data to improve vascular segmentation

no code implementations10 Oct 2019 Nima Tajbakhsh, Brian Lai, Shilpa Ananth, Xiaowei Ding

In this paper, we propose a segmentation framework called ErrorNet, which learns to correct these segmentation mistakes through the repeated process of injecting systematic segmentation errors to the segmentation result based on a learned shape prior, followed by attempting to predict the injected error.

Domain Adaptation Retinal Vessel Segmentation

Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation

no code implementations27 Aug 2019 Nima Tajbakhsh, Laura Jeyaseelan, Qian Li, Jeffrey Chiang, Zhihao Wu, Xiaowei Ding

The medical imaging literature has witnessed remarkable progress in high-performing segmentation models based on convolutional neural networks.

Medical Image Segmentation Semantic Segmentation

Automatic Segmentation of Pulmonary Lobes Using a Progressive Dense V-Network

no code implementations18 Feb 2019 Abdullah-Al-Zubaer Imran, Ali Hatamizadeh, Shilpa P. Ananth, Xiaowei Ding, Demetri Terzopoulos, Nima Tajbakhsh

We evaluated our model using 84 chest CT scans from the LIDC and 154 pathological cases from the LTRC datasets.

Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data

no code implementations25 Jan 2019 Nima Tajbakhsh, Yufei Hu, Junli Cao, Xingjian Yan, Yi Xiao, Yong Lu, Jianming Liang, Demetri Terzopoulos, Xiaowei Ding

We investigate the effectiveness of a simple solution to the common problem of deep learning in medical image analysis with limited quantities of labeled training data.

Colorization Transfer Learning

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