scholarly journals Deformable registration of the inflated and deflated lung for cone-beam CT-guided thoracic surgery

2012 ◽  
Author(s):  
Ali Uneri ◽  
Sajendra Nithiananthan ◽  
Sebastian Schafer ◽  
Yoshito Otake ◽  
J. Webster Stayman ◽  
...  
Keyword(s):  
Thoracic Surgery ◽  
Cone Beam Ct ◽  
Deformable Registration ◽  
Cone Beam ◽  
Ct Guided

scholarly journals Deformable registration of the inflated and deflated lung in cone-beam CT-guided thoracic surgery: Initial investigation of a combined model- and image-driven approach

2012 ◽  
Vol 40 (1) ◽  
pp. 017501 ◽  
Author(s):  
Ali Uneri ◽  
Sajendra Nithiananthan ◽  
Sebastian Schafer ◽  
Yoshito Otake ◽  
J. Webster Stayman ◽  
...  
Keyword(s):  
Thoracic Surgery ◽  
Cone Beam Ct ◽  
Deformable Registration ◽  
Cone Beam ◽  
Combined Model ◽  
Ct Guided ◽  
Initial Investigation

Using the Hybrid Operating Room in Thoracic Surgery

2018 ◽  
Vol 13 (5) ◽  
pp. 372-377 ◽  
Author(s):  
Carsten Schroeder ◽  
Jane M. Chung ◽  
Andrew B. Mitchell ◽  
Thomas A. Dillard ◽  
Alessandro G. Radaelli ◽  
...  
Keyword(s):  
Thoracic Surgery ◽  
Ct Scan ◽  
Cone Beam Ct ◽  
Percutaneous Biopsy ◽  
Cost Effective ◽  
Cone Beam ◽  
Ct Guided ◽  
Operation Room ◽  
Hybrid Operation ◽  
Site Evaluation

We describe the integration of the hybrid operation room cone-beam computed tomography (CT) scan technology into the practice of general thoracic surgery. The combination of the following three techniques: (1) cone-beam CT scan augmented navigational bronchoscopy, (2) cone-beam CT-guided percutaneous biopsy and/or fiducial placement, and (3) fiducial or image-guided video-assisted thoracic surgery resection, into a single-stage, single-provider procedure allows for diagnosis and treatment in one setting. Rapid on-site evaluation of cytological or pathology specimens is key to this “all-in-one” approach. The time from diagnosis to curative treatment can significantly be reduced using the hybrid operation room technology, leading to decreased upstaging, increased survival and facilitating the otherwise difficult intraoperative detection and resection of small and deeper lesions. Not only does this benefit the overall thoracic healthcare of the community but also provides a cost-effective paradigm for the institution.

Passive breath gating equipment for cone beam CT-guided RapidArc gastric cancer treatments

2015 ◽  
Vol 114 (1) ◽  
pp. 104-108 ◽  
Author(s):  
Weigang Hu ◽  
Guichao Li ◽  
Jinsong Ye ◽  
Jiazhou Wang ◽  
Jiayuan Peng ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cone Beam Ct ◽  
Cone Beam ◽  
Cancer Treatments ◽  
Ct Guided

scholarly journals Fluoroscopy and Cone-Beam CT–guided Fixation by Internal Cemented Screw for Pathologic Pelvic Fractures

Radiology ◽  
2019 ◽  
Vol 290 (2) ◽  
pp. 418-425 ◽  
Author(s):  
Charles Roux ◽  
Lambros Tselikas ◽  
Steven Yevich ◽  
Raphael Sandes Solha ◽  
Antoine Hakime ◽  
...  
Keyword(s):  
Cone Beam Ct ◽  
Pelvic Fractures ◽  
Cone Beam ◽  
Ct Guided

scholarly journals Fully Convolutional Network for Consistent Voxel-Wise Correspondence

2020 ◽  
Vol 34 (07) ◽  
pp. 12935-12942 ◽  
Author(s):  
Yungeng Zhang ◽  
Yuru Pei ◽  
Yuke Guo ◽  
Gengyu Ma ◽  
Tianmin Xu ◽  
...  
Keyword(s):  
Vector Fields ◽  
State Of The Art ◽  
Displacement Vector ◽  
Cone Beam Ct ◽  
Deformable Registration ◽  
Cone Beam ◽  
Nonlinear Mapping ◽  
Convolutional Network ◽  
Mapping Functions ◽  
Fully Convolutional Network

In this paper, we propose a fully convolutional network-based dense map from voxels to invertible pair of displacement vector fields regarding a template grid for the consistent voxel-wise correspondence. We parameterize the volumetric mapping using a convolutional network and train it in an unsupervised way by leveraging the spatial transformer to minimize the gap between the warped volumetric image and the template grid. Instead of learning the unidirectional map, we learn the nonlinear mapping functions for both forward and backward transformations. We introduce the combinational inverse constraints for the volumetric one-to-one maps, where the pairwise and triple constraints are utilized to learn the cycle-consistent correspondence maps between volumes. Experiments on both synthetic and clinically captured volumetric cone-beam CT (CBCT) images show that the proposed framework is effective and competitive against state-of-the-art deformable registration techniques.

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