Graph-convolutional-network-based interactive prostate segmentation in MR images.
Sign Up to like & getrecommendations! Published in 2020 at "Medical physics"
DOI: 10.1002/mp.14327
Abstract: PURPOSE Accurate and robust segmentation of the prostate from magnetic resonance (MR) images is extensively applied in many clinical applications in prostate cancer diagnosis and treatment. The purpose of this study is the development of… read more here.
Keywords: prostate; graph convolutional; segmentation; method ... See more keywords
Using the U‐net convolutional network to map forest types and disturbance in the Atlantic rainforest with very high resolution images
Sign Up to like & getrecommendations! Published in 2019 at "Remote Sensing in Ecology and Conservation"
DOI: 10.1002/rse2.111
Abstract: Using the U-net convolutional network to map forest types and disturbance in the Atlantic rainforest with very high resolution images Fabien H. Wagner, Alber Sanchez, Yuliya Tarabalka, Rodolfo G. Lotte, Matheus P. Ferreira, Marcos P.… read more here.
Keywords: using net; convolutional network; network map; map forest ... See more keywords
Hybrid approaches of convolutional network and support vector machine for American sign language prediction
Sign Up to like & getrecommendations! Published in 2019 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-019-7723-0
Abstract: The American Gesture based communication (ASL) is expressively helped for hard of hearing correspondence. Slowly gesture based communication use for the correspondence among open and the hard of hearing network. In this proposed framework another… read more here.
Keywords: approaches convolutional; network; support vector; hybrid approaches ... See more keywords
MVGCNMDA: Multi-view Graph Augmentation Convolutional Network for Uncovering Disease-Related Microbes.
Sign Up to like & getrecommendations! Published in 2022 at "Interdisciplinary sciences, computational life sciences"
DOI: 10.1007/s12539-022-00514-2
Abstract: MOTIVATION Exploring the interrelationships between microbes and disease can help microbiologists make decisions and plan treatments. Predicting new microbe-disease associations currently relies on biological experiments and domain knowledge, which is time-consuming and inefficient. Automated algorithms… read more here.
Keywords: augmentation; multi view; disease; convolutional network ... See more keywords
Pathologic liver tumor detection using feature aligned multi-scale convolutional network
Sign Up to like & getrecommendations! Published in 2022 at "Artificial intelligence in medicine"
DOI: 10.1016/j.artmed.2022.102244
Abstract: The detection of the most common type of liver tumor, that is, hepatocellular carcinoma (HCC), is one essential step to liver pathology image analysis. In liver tissue, common cell change phenomena such as apoptosis, necrosis,… read more here.
Keywords: scale convolutional; tumor; liver; detection ... See more keywords
Semantic segmentation via highly fused convolutional network with multiple soft cost functions
Sign Up to like & getrecommendations! Published in 2019 at "Cognitive Systems Research"
DOI: 10.1016/j.cogsys.2018.04.004
Abstract: Semantic image segmentation is one of the most challenged tasks in computer vision. In this paper, we propose a highly fused convolutional network, which consists of three parts: feature downsampling, combined feature upsampling and multiple… read more here.
Keywords: network; segmentation; multiple soft; highly fused ... See more keywords
Using graph convolutional network to characterize individuals with major depressive disorder across multiple imaging sites
Sign Up to like & getrecommendations! Published in 2022 at "EBioMedicine"
DOI: 10.1016/j.ebiom.2022.103977
Abstract: Summary Background Establishing objective and quantitative neuroimaging biomarkers at individual level can assist in early and accurate diagnosis of major depressive disorder (MDD). However, most previous studies using machine learning to identify MDD were based… read more here.
Keywords: depressive disorder; major depressive; graph convolutional; mdd ... See more keywords
Direct left-ventricular global longitudinal strain (GLS) computation with a fully convolutional network.
Sign Up to like & getrecommendations! Published in 2021 at "Journal of biomechanics"
DOI: 10.1016/j.jbiomech.2021.110878
Abstract: This study's purpose was to develop a direct MRI-based, deep-learning semantic segmentation approach for computing global longitudinal strain (GLS), a known metric for detecting left-ventricular (LV) cardiotoxicity in breast cancer. Displacement Encoding with Stimulated Echoes… read more here.
Keywords: fully convolutional; longitudinal strain; left ventricular; convolutional network ... See more keywords
Multi-layer convolutional network-based visual tracking via important region selection
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.07.010
Abstract: Abstract The convolutional network-based tracking (CNT) algorithm provides a training network with warped target regions in the first frame instead of large auxiliary datasets, which solves the problem of convolutional neural network (CNN)-based tracking requiring… read more here.
Keywords: network based; network; visual tracking; selection ... See more keywords
AEGCN: An Autoencoder-Constrained Graph Convolutional Network
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.12.061
Abstract: We propose a novel neural network architecture, called autoencoder-constrained graph convolutional network, to solve node classification task on graph domains. As suggested by its name, the core of this model is a convolutional network operating… read more here.
Keywords: graph convolutional; convolutional network; autoencoder constrained; network ... See more keywords
Synthesising KV-DRRs from MV-DRs with fractal hourglass convolutional network
Sign Up to like & getrecommendations! Published in 2018 at "Electronics Letters"
DOI: 10.1049/el.2017.4572
Abstract: During a radiation treatment, the images of kilovoltage digital reconstructed radiograph (KV-DRR) and megavoltage digital radiograph (MV-DR) are registered to guide the therapy. Such registration is difficult since the images belong to different modalities. To… read more here.
Keywords: network; hourglass; drs fractal; convolutional network ... See more keywords