Computational Methods and Clinical Applications for Spine Imaging, Kartoniert / Broschiert
Computational Methods and Clinical Applications for Spine Imaging
- 6th International Workshop and Challenge, CSI 2019, Shenzhen, China, October 17, 2019, Proceedings
- Publisher:
- Yunliang Cai, Liansheng Wang, Michel Audette, Guoyan Zheng, Shuo Li
- Publisher:
- Springer, 02/2020
- Binding:
- Kartoniert / Broschiert, Paperback
- Language:
- Englisch
- ISBN-13:
- 9783030397517
- Item number:
- 10121250
- Volume:
- 132 Pages
- Weight:
- 213 g
- Format:
- 235 x 155 mm
- Thickness:
- 7 mm
- Release date:
- 1.2.2020
- Note
-
Caution: Product is not in German language
Blurb
Regular Papers.- Detection of vertebral fractures in CT using 3D Convolutional Neural Networks.- Metastatic Vertebrae Segmentation for Use in a Clinical Pipeline.- Conditioned Variational Auto-Encoder for Detecting Osteoporotic Vertebral Fractures.- Vertebral Labelling in Radiographs: Learning a Coordinate Corrector to Enforce Spinal Shape.- Semi-supervised semantic segmentation of multiple lumbosacral structures on CT.- AASCE Challenge.- Accurate Automated Keypoint Detections for Spinal Curvature Estimation.- Seg4Reg Networks for Automated Spinal Curvature Estimation.- Automatic Spine Curvature Estimation by a Top-down Approach.- Automatic Cobb Angle Detection using Vertebra Detector and Vertebra Corners Regression.- Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaded Neural Networks.- Automated Spinal Curvature Assessment from X-Ray Images using Landmarks Estimation Network via Rotation Proposals.- A coarse-to-fine deep heatmap regression method for Adolescent Idiopathic Scoliosis Assessment.- Spinal Curve Guide Network(SCG-Net) for Accurate Automated Spinal Curvature Estimation.- A Multi-Task Learning Method for Direct Estimation of Spinal Curvature.