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MC-UNet Multi-module Concatenation based on U-shape Network for Retinal Blood Vessels Segmentation
[article]
2022
arXiv
pre-print
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A novel U-shaped network named Multi-module Concatenation which is based on Atrous convolution and multi-kernel pooling is put forward to retinal vessels segmentation in this paper. ...
Many deep learning frameworks have come up for retinal blood vessels segmentation tasks. ...
a novel U-shape network is proposed named Multi-module Concatenation U-Net (MC-UNet) based on atrous convolution and multi-kernel pooling for retinal vessels segmentation. ...
arXiv:2204.03213v1
fatcat:dw6lrbx2qrfcdlp7rae6cht5lu
Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future
2021
Sensors
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We also outline the limitations of existing techniques and discuss potential directions for future research. ...
We provide an overview of these methods in a systematic manner, organized by their domain of application including functional connectivity, anatomical structure, and electrical-based analysis. ...
[141] also incorporated a GCN into a unified CNN architecture for 2D vessel segmentation on retinal image datasets. ...
doi:10.3390/s21144758
fatcat:jytyt4u2pjgvhnhcto3vcvd3a4
Vision Transformers in Medical Computer Vision – A Contemplative Retrospection
[article]
2022
arXiv
pre-print
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We surveyed the application of Vision transformers in different areas of medical computer vision such as image-based disease classification, anatomical structure segmentation, registration, region-based ...
We hope that this review article will open future directions for researchers in medical computer vision. ...
[202] established a module MSAM, Multi model Spatial Attention Module, a deep learning based framework for lung tumor segmentation in PET-CT. ...
arXiv:2203.15269v1
fatcat:wecjpoikbvfz5cygytqpktoxdq
Myocardial Segmentation of Cardiac MRI Sequences With Temporal Consistency for Coronary Artery Disease Diagnosis
2022
Frontiers in Cardiovascular Medicine
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Coronary artery disease (CAD) is the most common cause of death globally, and its diagnosis is usually based on manual myocardial (MYO) segmentation of MRI sequences. ...
In this article, we propose a MYO segmentation framework for sequence of cardiac MRI (CMR) scanning images of the left ventricular (LV) cavity, right ventricular (RV) cavity, and myocardium. ...
Pyramid U-Net for retinal vessel segmentation. In: ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Toronto, ON: IEEE (2021). p. 1125–9. 27. ...
doi:10.3389/fcvm.2022.804442
pmid:35282363
pmcid:PMC8914019
fatcat:2w4jateounhydhs4kspxfozefa
Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future
[article]
2021
arXiv
pre-print
Preserved Fulltext
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The file type is application/pdf.
We also outline the limitations of existing techniques and discuss potential directions for future research. ...
We provide an overview of these methods in a systematic manner, organized by their domain of application including functional connectivity, anatomical structure and electrical-based analysis. ...
[187] also incorporated a GCN into a unified CNN architecture for 2D vessel segmentation on retinal image datasets. ...
arXiv:2105.13137v1
fatcat:gm7d2ziagba7bj3g34u4t3k43y
Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19
2020
Machine Vision and Applications
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Yet, coronavirus can be the real trigger to open the route for fast integration of DL in hospitals and medical centers. ...
Likewise, deep learning applications (DL) on pulmonary medical images emerged to achieve remarkable advances leading to promising clinical trials. ...
It proposed a model based on multi-stream multi-scale convolutional networks that aim to classify all nodule types without the need for any information. ...
doi:10.1007/s00138-020-01101-5
pmid:32834523
pmcid:PMC7386599
fatcat:tkkylrptc5hkpoj52hjs3kuttu
Advancing efficiency and robustness of neural networks for imaging
2020
Preserved Fulltext
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It investigates domain adaptation and introduces an architecture for adversarial networks tailored for adaptation of segmentation networks. ...
Moreover, it explores strategies for achieving robust performance on unseen data. ...
Contributions We present a fully automatic approach for lesion segmentation in multi-modal brain MRI based on an 11-layers deep, multi-scale, 3D CNN with the following main contributions: 1. ...
doi:10.25560/80157
fatcat:mv3q2zargfamrifgqwfycd53mq