☆ 3.8 Proceedings Paper

DA-Net: Dual Branch Transformer and Adaptive Strip Upsampling for Retinal Vessels Segmentation

MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION, MICCAI 2022, PT II (2022)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Multidisciplinary Sciences

PCAT-UNet: UNet-like network fused convolution and transformer for retinal vessel segmentation

Danny Chen et al.

Summary: The accurate segmentation of retinal vessels images is important for the diagnosis and monitoring of ophthalmic and systemic diseases. This paper proposes a PCAT-UNET method that combines Transformer and convolutional branches to effectively extract retinal micro vessels feature information, improving segmentation performance while enabling end-to-end training and rapid inference.

PLOS ONE (2022)

添加到收藏夹

Article Automation & Control Systems

Instance segmentation of biological images using graph convolutional network

Rongtao Xu et al.

Summary: Instance segmentation in biological images is a crucial task in the field of biological images and biomedical analysis. This paper proposes a novel method for segmentation of graph-guided instances in biological images. The method combines graph-guided feature fusion and gated spatial attention modules, and introduces a cluster distance loss to effectively distinguish foreground objects from similar backgrounds.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2022)

添加到收藏夹

Article Computer Science, Artificial Intelligence

SCS-Net: A Scale and Context Sensitive Network for Retinal Vessel Segmentation

Huisi Wu et al.

Summary: Segmenting retinal vessels accurately is crucial for detecting and diagnosing eye diseases, but it is challenging due to scale variations and complex anatomical contexts. This study proposes a novel scale and context sensitive network (SCS-Net) with modules like scale-aware feature aggregation and adaptive feature fusion to achieve better segmentation performance in challenging cases with large scale variations and complex context environments.

MEDICAL IMAGE ANALYSIS (2021)

添加到收藏夹

Proceedings Paper Engineering, Biomedical

RETINAL VESSEL SEGMENTATION VIA CONTEXT GUIDE ATTENTION NET WITH JOINT HARD SAMPLE MINING STRATEGY

Changwei Wang et al.

Summary: The proposed Context Guided Attention Module (CGAM) leverages surrounding context information and spatial attention to improve segmentation accuracy, while the Joint hard sample mining strategy (JHSM) addresses the issue of retinal vessel pixel imbalance. Experimental results on the publicly available DRIVE and CHASE_DB 1 datasets show that our model outperforms state-of-the-art methods.

2021 IEEE 18TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI) (2021)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

DC-Net: Dual Context Network for 2D Medical Image Segmentation

Rongtao Xu et al.

Summary: In this study, a Dual Context Network (DC-Net) is proposed for medical image segmentation, which can effectively aggregate global context and fuse multi-scale context information. Experimental results show that the method outperforms other advanced methods in skin lesion segmentation and cell contour segmentation tasks.

MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2021, PT I (2021)

添加到收藏夹

Article Radiology, Nuclear Medicine & Medical Imaging

SUD-GAN: Deep Convolution Generative Adversarial Network Combined with Short Connection and Dense Block for Retinal Vessel Segmentation

Tiejun Yang et al.

JOURNAL OF DIGITAL IMAGING (2020)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

CE-Net: Context Encoder Network for 2D Medical Image Segmentation

Zaiwang Gu et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2019)

添加到收藏夹

Article Engineering, Biomedical

Joint Segment-Level and Pixel-Wise Losses for Deep Learning Based Retinal Vessel Segmentation

Zengqiang Yan et al.

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2018)

添加到收藏夹

Article Engineering, Biomedical

A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images

Jose Ignacio Orlando et al.

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2017)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Blood vessel segmentation methodologies in retinal images - A survey

M. M. Fraz et al.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2012)

添加到收藏夹

Article Engineering, Biomedical

An Ensemble Classification-Based Approach Applied to Retinal Blood Vessel Segmentation

Muhammad Moazam Fraz et al.

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2012)

添加到收藏夹

Article Multidisciplinary Sciences

Fast Retinal Vessel Detection and Measurement Using Wavelets and Edge Location Refinement

Peter Bankhead et al.

PLOS ONE (2012)

添加到收藏夹

Article Biology

Retinal vessel extraction by matched filter with first-order derivative of Gaussian

Bob Zhang et al.

COMPUTERS IN BIOLOGY AND MEDICINE (2010)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Retinal blood vessel segmentation using line operators and support vector classification

Elisa Ricci et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2007)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Ridge-based vessel segmentation in color images of the retina

J Staal et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2004)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.