CT‐based automatic spine segmentation using patch‐based deep learning
CT vertebral segmentation plays an essential role in various clinical applications, such as
computer‐assisted surgical interventions, assessment of spinal abnormalities, and vertebral …
computer‐assisted surgical interventions, assessment of spinal abnormalities, and vertebral …
VerSe: a vertebrae labelling and segmentation benchmark for multi-detector CT images
Vertebral labelling and segmentation are two fundamental tasks in an automated spine
processing pipeline. Reliable and accurate processing of spine images is expected to …
processing pipeline. Reliable and accurate processing of spine images is expected to …
SpineParseNet: spine parsing for volumetric MR image by a two-stage segmentation framework with semantic image representation
S Pang, C Pang, L Zhao, Y Chen, Z Su… - … on Medical Imaging, 2020 - ieeexplore.ieee.org
Spine parsing (ie, multi-class segmentation of vertebrae and intervertebral discs (IVDs)) for
volumetric magnetic resonance (MR) image plays a significant role in various spinal disease …
volumetric magnetic resonance (MR) image plays a significant role in various spinal disease …
Iterative fully convolutional neural networks for automatic vertebra segmentation and identification
Precise segmentation and anatomical identification of the vertebrae provides the basis for
automatic analysis of the spine, such as detection of vertebral compression fractures or other …
automatic analysis of the spine, such as detection of vertebral compression fractures or other …
Deepvesselnet: Vessel segmentation, centerline prediction, and bifurcation detection in 3-d angiographic volumes
We present DeepVesselNet, an architecture tailored to the challenges faced when extracting
vessel trees and networks and corresponding features in 3-D angiographic volumes using …
vessel trees and networks and corresponding features in 3-D angiographic volumes using …
A computed tomography vertebral segmentation dataset with anatomical variations and multi-vendor scanner data
H Liebl, D Schinz, A Sekuboyina, L Malagutti… - Scientific data, 2021 - nature.com
With the advent of deep learning algorithms, fully automated radiological image analysis is
within reach. In spine imaging, several atlas-and shape-based as well as deep learning …
within reach. In spine imaging, several atlas-and shape-based as well as deep learning …
OP-convNet: a patch classification-based framework for CT vertebrae segmentation
Accurate vertebrae segmentation from medical images plays an important role in clinical
tasks of surgical planning, diagnosis, kyphosis, scoliosis, degenerative disc disease …
tasks of surgical planning, diagnosis, kyphosis, scoliosis, degenerative disc disease …
SVseg: Stacked sparse autoencoder-based patch classification modeling for vertebrae segmentation
Precise vertebrae segmentation is essential for the image-related analysis of spine
pathologies such as vertebral compression fractures and other abnormalities, as well as for …
pathologies such as vertebral compression fractures and other abnormalities, as well as for …
Automatic vertebrae localization and segmentation in CT with a two-stage Dense-U-Net
P Cheng, Y Yang, H Yu, Y He - Scientific Reports, 2021 - nature.com
Automatic vertebrae localization and segmentation in computed tomography (CT) are
fundamental for spinal image analysis and spine surgery with computer-assisted surgery …
fundamental for spinal image analysis and spine surgery with computer-assisted surgery …
[PDF][PDF] Coarse to Fine Vertebrae Localization and Segmentation with SpatialConfiguration-Net and U-Net.
Localization and segmentation of vertebral bodies from spine CT volumes are crucial for
pathological diagnosis, surgical planning, and postoperative assessment. However, fully …
pathological diagnosis, surgical planning, and postoperative assessment. However, fully …