Search results for "3D deep learning models"

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Automatic Segmentation Using a Hybrid Dense Network Integrated With an 3D-Atrous Spatial Pyramid Pooling Module for Computed Tomography (CT) Imaging

2020

Computed tomography (CT) with a contrast-enhanced imaging technique is extensively proposed for the assessment and segmentation of multiple organs, especially organs at risk. It is an important factor involved in the decision making in clinical applications. Automatic segmentation and extraction of abdominal organs, such as thoracic organs at risk, from CT images are challenging tasks due to the low contrast of pixel values surrounding other organs. Various deep learning models based on 2D and 3D convolutional neural networks have been proposed for the segmentation of medical images because of their automatic feature extraction capability based on large labeled datasets. In this paper, we p…

SegTHOR0209 industrial biotechnologyGeneral Computer ScienceComputer scienceFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyConvolutional neural network020901 industrial engineering & automationPyramid0202 electrical engineering electronic engineering information engineeringMedical imagingGeneral Materials ScienceSegmentationPyramid (image processing)3D deep learning modelsPixelbusiness.industryDeep learningGeneral EngineeringPattern recognition3D-atrous spatial pyramid pooling (ASPP)Feature (computer vision)3D volumetric segmentation020201 artificial intelligence & image processinglcsh:Electrical engineering. Electronics. Nuclear engineeringArtificial intelligencebusinesslcsh:TK1-9971IEEE Access
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