Segmentation of Liver Anatomy by Combining 3D U-Net Approaches
Applied Sciences, 2021 Accurate liver vessel segmentation is of crucial importance for the clinical diagnosis and treatment of many hepatic diseases. Recent state-of-the-art methods for liver vessel reconstruction mostly utilize deep learning methods, namely, the U-Net model ...
Abir Affane +6 more
doaj +2 more sources
Automated segmentation of vertebral cortex with 3D U-Net-based deep convolutional neural network [PDF]
Frontiers in Bioengineering and Biotechnology, 2022 Objectives: We developed a 3D U-Net-based deep convolutional neural network for the automatic segmentation of the vertebral cortex. The purpose of this study was to evaluate the accuracy of the 3D U-Net deep learning model.Methods: In this study, a fully
Yang Li +8 more
doaj +2 more sources
Spider U-Net: Incorporating Inter-Slice Connectivity Using LSTM for 3D Blood Vessel Segmentation
Applied Sciences, 2021 Blood vessel segmentation (BVS) of 3D medical imaging such as computed tomography and magnetic resonance angiography (MRA) is an essential task in the clinical field.
Kyeorye Lee +3 more
doaj +2 more sources
Automated Skull Stripping in Mouse Functional Magnetic Resonance Imaging Analysis Using 3D U-Net [PDF]
Frontiers in Neuroscience, 2022 Skull stripping is an initial and critical step in the pipeline of mouse fMRI analysis. Manual labeling of the brain usually suffers from intra- and inter-rater variability and is highly time-consuming.
Guohui Ruan +26 more
doaj +2 more sources
Attention 3D U-Net with Multiple Skip Connections for Segmentation of Brain Tumor Images [PDF]
Sensors, 2022 Among researchers using traditional and new machine learning and deep learning techniques, 2D medical image segmentation models are popular. Additionally, 3D volumetric data recently became more accessible, as a result of the high number of studies ...
Jakhongir Nodirov +2 more
doaj +2 more sources
A COMPARATIVE STUDY OF DEEP ARCHITECTURES FOR VOXEL SEGMENTATION IN VOLUME IMAGES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 This study investigates the performance of eight different deep learning architectures for voxel segmentation in volume images. The motivation is to segment carbon in carbon reinforced concrete (CRC) in micro-tomography (μ-CT) data. Although there are
F. Wagner, H.-G. Maas
doaj +1 more source
Fully automated condyle segmentation using 3D convolutional neural networks
Scientific Reports, 2022 The aim of this study was to develop an auto-segmentation algorithm for mandibular condyle using the 3D U-Net and perform a stress test to determine the optimal dataset size for achieving clinically acceptable accuracy.
Nayansi Jha +6 more
doaj +1 more source
Design of lung nodules segmentation and recognition algorithm based on deep learning
BMC Bioinformatics, 2021 Background Accurate segmentation and recognition algorithm of lung nodules has great important value of reference for early diagnosis of lung cancer.
Hui Yu +5 more
doaj +1 more source
3D U-Net Improves Automatic Brain Extraction for Isotropic Rat Brain Magnetic Resonance Imaging Data
Frontiers in Neuroscience, 2021 Brain extraction is a critical pre-processing step in brain magnetic resonance imaging (MRI) analytical pipelines. In rodents, this is often achieved by manually editing brain masks slice-by-slice, a time-consuming task where workloads increase with ...
Li-Ming Hsu +15 more
doaj +1 more source
IET Computer Vision, 2021 Three‐dimensional (3D) shape reconstruction of objects requires multiple scans and complex reconstruction algorithms. An alternative approach is to infer the 3D shape of an object from a single depth image (i.e. single depth view).
Edwin Valarezo Añazco +2 more
doaj +1 more source