End-To-End Convolutional Neural Network for 3D Reconstruction of Knee Bones from Bi-planar X-Ray Images
- 21 October 2020
- book chapter
- conference paper
- Published by Springer Science and Business Media LLC in Lecture Notes in Computer Science
Abstract
No abstract availableThis publication has 24 references indexed in Scilit:
- Using Bi-planar X-Ray Images to Reconstruct the Spine Structure by the Convolution Neural NetworkIFMBE Proceedings (IFMBE), 2019
- Multiclass Weighted Loss for Instance Segmentation of Cluttered CellsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2018
- Single‐image Tomography: 3D Volumes from 2D Cranial X‐RaysComputer Graphics Forum, 2018
- Fundamental Matrices from Moving Objects Using Line Motion BarcodesPublished by Springer Science and Business Media LLC ,2016
- 3D-R2N2: A Unified Approach for Single and Multi-view 3D Object ReconstructionLecture Notes in Computer Science, 2016
- Camera Calibration from Dynamic Silhouettes Using Motion BarcodesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2016
- Fast Generation of Virtual X-ray Images for Reconstruction of 3D AnatomyIEEE Transactions on Visualization and Computer Graphics, 2013
- 2D–3D shape reconstruction of the distal femur from stereo X-ray imaging using statistical shape modelsMedical Image Analysis, 2011
- 3D shape reconstruction of bone from two x-ray images using 2D/3D non-rigid registration based on moving least-squares deformationPublished by SPIE-Intl Soc Optical Eng ,2010
- Active Shape Models-Their Training and ApplicationComputer Vision and Image Understanding, 1995